Instruction and logic for Boyer-Moore search of text strings

ABSTRACT

Instructions and logic provide extended vector suffix comparisons for Boyer-Moore searches. Some embodiments, responsive to an instruction specifying: a pattern source operand and a target source operand, compare each of m data elements of the pattern operand with each data element of the target operand. A first and second equal ordered aggregation operation are performed from the comparisons according to the m data elements of the pattern source operand. A result of the first and second aggregation operations indicating whether or not a possible match exists between the m data elements of the pattern source operand and d data element positions relative to data elements of the target source operand is stored. Ordering of the data elements of the pattern and the target operands may be reversed for the second aggregation operation, and d may be a sum of m−1 and the quantity of target operand elements in some embodiments.

RELATED APPLICATIONS

This is a Continuation of application Ser. No. 13/632,075, filed Sep.30, 2012, now U.S. Pat. No. 9,268,567, issued Feb. 23, 2016.

FIELD OF THE DISCLOSURE

The present disclosure pertains to the field of processing logic,microprocessors, and associated instruction set architecture that, whenexecuted by the processor or other processing logic, perform logical,mathematical, or other functional operations. In particular, thedisclosure relates to extended vector suffix comparison instructions andlogic for Boyer-Moore searches of text strings.

BACKGROUND OF THE DISCLOSURE

Computer systems have become increasingly pervasive in our society. Theprocessing capabilities of computers have increased the efficiency andproductivity of workers in a wide spectrum of professions. As the costsof purchasing and owning a computer continues to drop, more and moreconsumers have been able to take advantage of newer and faster machines.Furthermore, many people enjoy the use of notebook computers because ofthe freedom. Mobile computers allow users to easily transport their dataand work with them as they leave the office or travel. This scenario isquite familiar with marketing staff, corporate executives, and evenstudents.

As processor technology advances, newer software code is also beinggenerated to run on machines with these processors. Users generallyexpect and demand higher performance from their computers regardless ofthe type of software being used. One such issue can arise from the kindsof instructions and operations that are actually being performed withinthe processor. Certain types of operations require more time to completebased on the complexity of the operations and/or type of circuitryneeded. This provides an opportunity to optimize the way certain complexoperations are executed inside the processor.

Communications applications have been driving microprocessor developmentfor more than a decade. In fact, the line between computing andcommunication has become increasingly blurred due, in part, to the useof textual communication applications. Textual applications arepervasive within consumer segments, and among numerous devices, fromcell phones to personal computers, requiring faster and fasterprocessing of text information. Textual communication devices continueto find their way into computing and communication devices in the formof applications, such as Microsoft® Instant Messenger™, emailapplications, such as Microsoft® Outlook™, and cell phone textingapplications. As a result, tomorrow's personal computing andcommunications experience will be even richer in textual capability.

Accordingly, the processing or parsing of text information communicatedbetween computing or communication devices has become increasinglyimportant for current computing and communication devices. Particularly,interpretation by a communication or computing device of strings of textinformation include some of the most important operations performed ontext data.

The Boyer-Moore string search algorithm is an efficient string searchingalgorithm that is a standard benchmark for practical string searchesdeveloped by Robert S. Boyer and J Strother Moore in 1977. The algorithmpreprocesses the string being searched for (the pattern), but not thestring being searched in (the text). It is well-suited for applicationsin which the text does not persist across multiple searches. TheBoyer-Moore algorithm uses information gathered during the preprocessstep to skip sections of the text, resulting in a lower constant factorthan many other string search algorithms. In general, the algorithm runsfaster as the pattern length increases.

Search operations on strings of text information may be computationallyintensive, but offer a high level of data parallelism that can beexploited through an efficient implementation using various data storagedevices, such as for example, single instruction multiple data (SIMD)registers. Vectorized searches have been implemented in variouslibraries, e.g., using single instruction multiple data SIMDinstructions. For example, Streaming SIMD Extension 4 (SSE4) for certainIntel® architecture processors, and particularly SSE4.2, includes SIMDinstructions that perform character searches and comparisons on twooperands of a particular number of bytes (e.g., sixteen) at a time. Somecurrent architectures require multiple operations, instructions, orsub-instructions (often referred to as “micro-operations” or “uops”) toperform various logical and mathematical operations on a number ofoperands, thereby diminishing throughput and increasing the number ofclock cycles required to perform the logical and mathematicaloperations.

For example, an instruction sequence consisting of a number ofinstructions may be required to perform one or more operations necessaryto interpret particular words of a text string, including comparing twoor more text words represented by various datatypes within a processingapparatus, system or computer program. However, such prior arttechniques may require numerous processing cycles or extra instructions,and thus may cause a processor or system to consume unnecessary powerand/or processing cycles in order to generate their results.Furthermore, some prior art techniques may require additional processingof data during the search to be useful in standard benchmarks forpractical string searches such as a Boyer-Moore string search.

To date, potential solutions to such performance and efficiency limitingissues have not been adequately explored.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and notlimitation in the figures of the accompanying drawings.

FIG. 1A is a block diagram of one embodiment of a system that executesinstructions to provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 1B is a block diagram of another embodiment of a system thatexecutes instructions to provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 1C is a block diagram of another embodiment of a system thatexecutes instructions to provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 2 is a block diagram of one embodiment of a processor that executesinstructions to provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 3A illustrates packed data types according to one embodiment.

FIG. 3B illustrates packed data types according to one embodiment.

FIG. 3C illustrates packed data types according to one embodiment.

FIG. 3D illustrates an instruction encoding to provide extended vectorsuffix comparisons for Boyer-Moore searches according to one embodiment.

FIG. 3E illustrates an instruction encoding to provide extended vectorsuffix comparisons for Boyer-Moore searches according to anotherembodiment.

FIG. 3F illustrates an instruction encoding to provide extended vectorsuffix comparisons for Boyer-Moore searches according to anotherembodiment.

FIG. 3G illustrates an instruction encoding to provide extended vectorsuffix comparisons for Boyer-Moore searches according to anotherembodiment.

FIG. 3H illustrates an instruction encoding to provide extended vectorsuffix comparisons for Boyer-Moore searches according to anotherembodiment.

FIG. 4A illustrates elements of one embodiment of a processormicro-architecture to execute instructions that provide extended vectorsuffix comparisons for Boyer-Moore searches.

FIG. 4B illustrates elements of another embodiment of a processormicro-architecture to execute instructions that provide extended vectorsuffix comparisons for Boyer-Moore searches.

FIG. 5 is a block diagram of one embodiment of a processor to executeinstructions that provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 6 is a block diagram of one embodiment of a computer system toexecute instructions that provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 7 is a block diagram of another embodiment of a computer system toexecute instructions that provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 8 is a block diagram of another embodiment of a computer system toexecute instructions that provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 9 is a block diagram of one embodiment of a system-on-a-chip toexecute instructions that provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 10 is a block diagram of an embodiment of a processor to executeinstructions that provide extended vector suffix comparisons forBoyer-Moore searches.

FIG. 11 is a block diagram of one embodiment of an IP core developmentsystem that provides extended vector suffix comparisons for Boyer-Mooresearches.

FIG. 12 illustrates one embodiment of an architecture emulation systemthat provides extended vector suffix comparisons for Boyer-Mooresearches.

FIG. 13 illustrates one embodiment of a system to translate instructionsthat provide extended vector suffix comparisons for Boyer-Mooresearches.

FIG. 14A schematically illustrates an example searching technique inaccordance with various embodiments that provide extended vector suffixcomparisons for Boyer-Moore searches.

FIG. 14B illustrates an embodiment of an apparatus to provide extendedvector suffix comparisons for Boyer-Moore searches.

FIG. 15A schematically illustrates an alternative example searchingtechnique in accordance with various embodiments that provide extendedvector suffix comparisons for Boyer-Moore searches.

FIG. 15B illustrates an alternative embodiment of an apparatus toprovide extended vector suffix comparisons for Boyer-Moore searches.

FIG. 16 illustrates a flow diagram for one embodiment of a process toprovide extended vector suffix comparisons for Boyer-Moore searches.

FIG. 17 illustrates a flow diagram for an alternative embodiment of aprocess to provide extended vector suffix comparisons for Boyer-Mooresearches.

FIG. 18 illustrates a flow diagram for another alternative embodiment ofa process to provide extended vector suffix comparisons for Boyer-Mooresearches.

DETAILED DESCRIPTION

The following description discloses instructions and processing logic toprovide extended vector suffix comparisons for Boyer-Moore searcheswithin or in association with a processor, computer system, or otherprocessing apparatus.

Multiple variants of the Boyer-Moore algorithm, such theBoyer-Moore-Horspool algorithm, may be used for pattern searching. SomeBoyer-Moore algorithm variants may employ a lookup table (sometimesreferred to as a “bad character table”) to determine a sliding windowshift distance where the pattern is not found in a current slidingwindow. Boyer-Moore variants may perform granular comparisons of datawith the pattern, e.g., byte-to-byte or N-gram data unit to N-gram dataunit, to determine whether a match is found. The sliding window shiftdistance in Boyer-Moore variants may be limited by a length of thepattern. Many Boyer-Moore variants operate in accordance with thefollowing abstract pseudo code:

 create bad character table; [optionally, create second table;] setsliding window to beginning of data to be searched; do  if tailverification fails {   use bad character table to determine shiftdistance of sliding window, and   shift sliding window;  } else { //tailverification passes   perform various operations to determine whetherthere is a complete   pattern match;   return pattern found or shiftsliding window;  } until pattern found or no more data to be searched;

The “various operations” that may be performed to determine whetherthere is a complete pattern match may vary according to the variant ofBoyer-Moore being used, and are not material for this disclosure.Moreover, assuming a complete pattern match is not found after tailverification passes, the sliding window may be shifted in conventionalways, including but not limited to shifting the sliding window one dataunit (e.g., as may be done in the Boyer-Moore-Horspool algorithm), or byimplementing a second table that predicts the shift distance after amulti-data-point-partial-match false verification.

Conventional Boyer-Moore variants use scalar comparators to scan for apattern match. This may limit a shift distance between consecutivesliding windows to no more than a length m of a suffix of a searchpattern P, e.g. that can fit into a register operand for comparisons.Moreover, data units such as bytes or N-grams may be compared one at atime, which may cause pattern searching performance to be, at best,linear with the pattern length. Additionally, in conventionalBoyer-Moore variants, the shift distances predicted by the bad-charactertable in the event of a tail-verification error are often less than thepattern suffix length m. Boyer-Moore techniques that reduce slidingwindow shift distances, e.g., to one data unit, may cause a reduction ofmaximum shift distance and higher cost in data access latency.

Accordingly, various methods and techniques are described herein forperforming vectorized searches to locate a pattern P having a length mwithin a set of data T. In various embodiments, the vectorized searchmay include a shift of a sliding window into T by a distance d that isgreater than m on determination, based on one or more ordered vectorizedcomparisons of portions of P and T, that no potential match of P isfound within the sliding window. An “ordered vector comparison” mayrefer to any multi-data unit comparison that occurs in a particularorder. For example, “forward” and “reverse” vector comparisons arediscussed herein.

In various embodiments, the one or more ordered vectorized comparisonsmay include one or more SIMD instructions supported by a processor.These vectorized SIMD instructions may be incorporated into BM variantsin various ways in order to speed up pattern searching. For example, anumber of “false positives” may be reduced from that which might befound using non-vectorized instructions, e.g., instructions that compareone data unit at a time. Additionally or alternatively, the use ofvectorized SIMD instructions may require fewer sliding window shiftsthan a non-vectorized BM pattern search, as the use of such vectorizedinstructions may enable sliding window shifts of a distance d that isgreater than a length m of a search pattern P.

Disclosed herein in various embodiments, are instructions and logic forBoyer-Moore vectorized searches of text strings. In some embodiments,instructions and logic provide extended vector suffix comparisons.Responsive to an instruction specifying: a pattern source operand and atarget source operand, each of m data elements of the pattern operandare compared with each data element of the target operand. A first equalordered aggregation operation and a second equal ordered aggregationoperation are performed from the comparisons according to the m dataelements of the pattern source operand. A result of the first and secondaggregation operations is stored indicating whether or not a possiblematch exists between the m data elements of the pattern source operandand d data element positions relative to n data elements of the targetsource operand. Ordering of the data elements of the pattern and thetarget operands may be reversed for the second aggregation operation,and d may be a sum of m−1 and the quantity, n, of target operandelements in some embodiments. In some cases where m elements of thepattern operand are compared with n elements of the target operand, dmay be up to n+m−1.

It will be appreciated that pattern searches for Boyer-Moore searchesmay be supported through executable machine instructions according tosome embodiments of extended vector suffix comparisons, and thereforemay require less overall sliding window shifts than a conventionalBoyer-Moore pattern searching algorithm. It will also be appreciatedthat some embodiments may support extended vector suffix comparisons forBoyer-Moore searches without significantly increasing implementationcosts. As will be shown in greater detail below, an instruction such asan extended forward-reverse vector suffix comparison instruction, forexample, may be implemented with relatively little additional hardwareor alternatively by a sequence of micro-operations in some embodiments,including for example, one or more micro-operations to reverse theordering of data elements of both the pattern source operand and thetarget source operand, and a plurality of micro-operations to performpacked comparisons of strings with equal ordered aggregation on theoriginal ordering and on the reversed ordering. An instruction such asan extended two-forward vector suffix comparison instruction, as anotherexample, may be implemented with relatively little additional hardwareor alternatively by a sequence of micro-operations in some embodiments,including for example, a plurality of micro-operations to perform packedcomparisons of strings with equal ordered aggregation. Thus, withrelatively little additional hardware, extended vector suffix comparisonfunctionality may be provided, in such a way that design tradeoffs maybe made between processing speed, power consumption, die area, etc.

In the following description, numerous specific details such asprocessing logic, processor types, micro-architectural conditions,events, enablement mechanisms, and the like are set forth in order toprovide a more thorough understanding of embodiments of the presentinvention. It will be appreciated, however, by one skilled in the artthat the invention may be practiced without such specific details.Additionally, some well known structures, circuits, and the like havenot been shown in detail to avoid unnecessarily obscuring embodiments ofthe present invention.

Although the following embodiments are described with reference to aprocessor, other embodiments are applicable to other types of integratedcircuits and logic devices. Similar techniques and teachings ofembodiments of the present invention can be applied to other types ofcircuits or semiconductor devices that can benefit from higher pipelinethroughput and improved performance. The teachings of embodiments of thepresent invention are applicable to any processor or machine thatperforms data manipulations. However, the present invention is notlimited to processors or machines that perform 512 bit, 256 bit, 128bit, 64 bit, 32 bit, or 16 bit data operations and can be applied to anyprocessor and machine in which manipulation or management of data isperformed. In addition, the following description provides examples, andthe accompanying drawings show various examples for the purposes ofillustration. However, these examples should not be construed in alimiting sense as they are merely intended to provide examples ofembodiments of the present invention rather than to provide anexhaustive list of all possible implementations of embodiments of thepresent invention.

Although the below examples describe instruction handling anddistribution in the context of execution units and logic circuits, otherembodiments of the present invention can be accomplished by way of adata or instructions stored on a machine-readable, tangible medium,which when performed by a machine cause the machine to perform functionsconsistent with at least one embodiment of the invention. In oneembodiment, functions associated with embodiments of the presentinvention are embodied in machine-executable instructions. Theinstructions can be used to cause a general-purpose or special-purposeprocessor that is programmed with the instructions to perform the stepsof the present invention. Embodiments of the present invention may beprovided as a computer program product or software which may include amachine or computer-readable medium having stored thereon instructionswhich may be used to program a computer (or other electronic devices) toperform one or more operations according to embodiments of the presentinvention. Alternatively, steps of embodiments of the present inventionmight be performed by specific hardware components that containfixed-function logic for performing the steps, or by any combination ofprogrammed computer components and fixed-function hardware components.

Instructions used to program logic to perform embodiments of theinvention can be stored within a memory in the system, such as DRAM,cache, flash memory, or other storage. Furthermore, the instructions canbe distributed via a network or by way of other computer readable media.Thus a machine-readable medium may include any mechanism for storing ortransmitting information in a form readable by a machine (e.g., acomputer), but is not limited to, floppy diskettes, optical disks,Compact Disc, Read-Only Memory (CD-ROMs), and magneto-optical disks,Read-Only Memory (ROMs), Random Access Memory (RAM), ErasableProgrammable Read-Only Memory (EPROM), Electrically ErasableProgrammable Read-Only Memory (EEPROM), magnetic or optical cards, flashmemory, or a tangible, machine-readable storage used in the transmissionof information over the Internet via electrical, optical, acoustical orother forms of propagated signals (e.g., carrier waves, infraredsignals, digital signals, etc.). Accordingly, the computer-readablemedium includes any type of tangible machine-readable medium suitablefor storing or transmitting electronic instructions or information in aform readable by a machine (e.g., a computer).

A design may go through various stages, from creation to simulation tofabrication. Data representing a design may represent the design in anumber of manners. First, as is useful in simulations, the hardware maybe represented using a hardware description language or anotherfunctional description language. Additionally, a circuit level modelwith logic and/or transistor gates may be produced at some stages of thedesign process. Furthermore, most designs, at some stage, reach a levelof data representing the physical placement of various devices in thehardware model. In the case where conventional semiconductor fabricationtechniques are used, the data representing the hardware model may be thedata specifying the presence or absence of various features on differentmask layers for masks used to produce the integrated circuit. In anyrepresentation of the design, the data may be stored in any form of amachine readable medium. A memory or a magnetic or optical storage suchas a disc may be the machine readable medium to store informationtransmitted via optical or electrical wave modulated or otherwisegenerated to transmit such information. When an electrical carrier waveindicating or carrying the code or design is transmitted, to the extentthat copying, buffering, or re-transmission of the electrical signal isperformed, a new copy is made. Thus, a communication provider or anetwork provider may store on a tangible, machine-readable medium, atleast temporarily, an article, such as information encoded into acarrier wave, embodying techniques of embodiments of the presentinvention.

In modern processors, a number of different execution units are used toprocess and execute a variety of code and instructions. Not allinstructions are created equal as some are quicker to complete whileothers can take a number of clock cycles to complete. The faster thethroughput of instructions, the better the overall performance of theprocessor. Thus it would be advantageous to have as many instructionsexecute as fast as possible. However, there are certain instructionsthat have greater complexity and require more in terms of execution timeand processor resources. For example, there are floating pointinstructions, load/store operations, data moves, etc.

As more computer systems are used in internet, text, and multimediaapplications, additional processor support has been introduced overtime. In one embodiment, an instruction set may be associated with oneor more computer architectures, including data types, instructions,register architecture, addressing modes, memory architecture, interruptand exception handling, and external input and output (I/O).

In one embodiment, the instruction set architecture (ISA) may beimplemented by one or more micro-architectures, which includes processorlogic and circuits used to implement one or more instruction sets.Accordingly, processors with different micro-architectures can share atleast a portion of a common instruction set. For example, Intel® Pentium4 processors, Intel® Core™ processors, and processors from AdvancedMicro Devices, Inc. of Sunnyvale Calif. implement nearly identicalversions of the x86 instruction set (with some extensions that have beenadded with newer versions), but have different internal designs.Similarly, processors designed by other processor development companies,such as ARM Holdings, Ltd., MIPS, or their licensees or adopters, mayshare at least a portion a common instruction set, but may includedifferent processor designs. For example, the same register architectureof the ISA may be implemented in different ways in differentmicro-architectures using new or well-known techniques, includingdedicated physical registers, one or more dynamically allocated physicalregisters using a register renaming mechanism (e.g., the use of aRegister Alias Table (RAT), a Reorder Buffer (ROB) and a retirementregister file. In one embodiment, registers may include one or moreregisters, register architectures, register files, or other registersets that may or may not be addressable by a software programmer.

In one embodiment, an instruction may include one or more instructionformats. In one embodiment, an instruction format may indicate variousfields (number of bits, location of bits, etc.) to specify, among otherthings, the operation to be performed and the operand(s) on which thatoperation is to be performed. Some instruction formats may be furtherbroken defined by instruction templates (or sub formats). For example,the instruction templates of a given instruction format may be definedto have different subsets of the instruction format's fields and/ordefined to have a given field interpreted differently. In oneembodiment, an instruction is expressed using an instruction format(and, if defined, in a given one of the instruction templates of thatinstruction format) and specifies or indicates the operation and theoperands upon which the operation will operate.

Scientific, financial, auto-vectorized general purpose, RMS(recognition, mining, and synthesis), and visual and multimediaapplications (e.g., 2D/3D graphics, image processing, videocompression/decompression, voice recognition algorithms and audiomanipulation) may require the same operation to be performed on a largenumber of data items. In one embodiment, Single Instruction MultipleData (SIMD) refers to a type of instruction that causes a processor toperform an operation on multiple data elements. SIMD technology may beused in processors that can logically divide the bits in a register intoa number of fixed-sized or variable-sized data elements, each of whichrepresents a separate value. For example, in one embodiment, the bits ina 64-bit register may be organized as a source operand containing fourseparate 16-bit data elements, each of which represents a separate16-bit value. This type of data may be referred to as ‘packed’ data typeor ‘vector’ data type, and operands of this data type are referred to aspacked data operands or vector operands. In one embodiment, a packeddata item or vector may be a sequence of packed data elements storedwithin a single register, and a packed data operand or a vector operandmay be a source or destination operand of a SIMD instruction (or ‘packeddata instruction’ or a ‘vector instruction’). In one embodiment, a SIMDinstruction specifies a single vector operation to be performed on twosource vector operands to generate a destination vector operand (alsoreferred to as a result vector operand) of the same or different size,with the same or different number of data elements, and in the same ordifferent data element order.

SIMD technology, such as that employed by the Intel® Core™ processorshaving an instruction set including x86, MMX™, Streaming SIMD Extensions(SSE), SSE2, SSE3, SSE4.1, and SSE4.2 instructions, ARM processors, suchas the ARM Cortex® family of processors having an instruction setincluding the Vector Floating Point (VFP) and/or NEON instructions, andMIPS processors, such as the Loongson family of processors developed bythe Institute of Computing Technology (ICT) of the Chinese Academy ofSciences, has enabled a significant improvement in applicationperformance (Core™ and MMX™ are registered trademarks or trademarks ofIntel Corporation of Santa Clara, Calif.).

In one embodiment, destination and source registers/data are genericterms to represent the source and destination of the corresponding dataor operation. In some embodiments, they may be implemented by registers,memory, or other storage areas having other names or functions thanthose depicted. For example, in one embodiment, “DEST1” may be atemporary storage register or other storage area, whereas “SRC1” and“SRC2” may be a first and second source storage register or otherstorage area, and so forth. In other embodiments, two or more of the SRCand DEST storage areas may correspond to different data storage elementswithin the same storage area (e.g., a SIMD register). In one embodiment,one of the source registers may also act as a destination register by,for example, writing back the result of an operation performed on thefirst and second source data to one of the two source registers servingas a destination registers.

FIG. 1A is a block diagram of an exemplary computer system formed with aprocessor that includes execution units to execute an instruction inaccordance with one embodiment of the present invention. System 100includes a component, such as a processor 102 to employ execution unitsincluding logic to perform algorithms for process data, in accordancewith the present invention, such as in the embodiment described herein.System 100 is representative of processing systems based on the PENTIUM®III, PENTIUM® 4, Xeon™, Itanium®, XScale™ and/or StrongARM™microprocessors available from Intel Corporation of Santa Clara, Calif.,although other systems (including PCs having other microprocessors,engineering workstations, set-top boxes and the like) may also be used.In one embodiment, sample system 100 may execute a version of theWINDOWS™ operating system available from Microsoft Corporation ofRedmond, Wash., although other operating systems (UNIX and Linux forexample), embedded software, and/or graphical user interfaces, may alsobe used. Thus, embodiments of the present invention are not limited toany specific combination of hardware circuitry and software.

Embodiments are not limited to computer systems. Alternative embodimentsof the present invention can be used in other devices such as handhelddevices and embedded applications. Some examples of handheld devicesinclude cellular phones, Internet Protocol devices, digital cameras,personal digital assistants (PDAs), and handheld PCs. Embeddedapplications can include a micro controller, a digital signal processor(DSP), system on a chip, network computers (NetPC), set-top boxes,network hubs, wide area network (WAN) switches, or any other system thatcan perform one or more instructions in accordance with at least oneembodiment.

FIG. 1A is a block diagram of a computer system 100 formed with aprocessor 102 that includes one or more execution units 108 to performan algorithm to perform at least one instruction in accordance with oneembodiment of the present invention. One embodiment may be described inthe context of a single processor desktop or server system, butalternative embodiments can be included in a multiprocessor system.System 100 is an example of a ‘hub’ system architecture. The computersystem 100 includes a processor 102 to process data signals. Theprocessor 102 can be a complex instruction set computer (CISC)microprocessor, a reduced instruction set computing (RISC)microprocessor, a very long instruction word (VLIW) microprocessor, aprocessor implementing a combination of instruction sets, or any otherprocessor device, such as a digital signal processor, for example. Theprocessor 102 is coupled to a processor bus 110 that can transmit datasignals between the processor 102 and other components in the system100. The elements of system 100 perform their conventional functionsthat are well known to those familiar with the art.

In one embodiment, the processor 102 includes a Level 1 (L1) internalcache memory 104. Depending on the architecture, the processor 102 canhave a single internal cache or multiple levels of internal cache.Alternatively, in another embodiment, the cache memory can resideexternal to the processor 102. Other embodiments can also include acombination of both internal and external caches depending on theparticular implementation and needs. Register file 106 can storedifferent types of data in various registers including integerregisters, floating point registers, status registers, and instructionpointer register.

Execution unit 108, including logic to perform integer and floatingpoint operations, also resides in the processor 102. The processor 102also includes a microcode (ucode) ROM that stores microcode for certainmacroinstructions. For one embodiment, execution unit 108 includes logicto handle a packed instruction set 109. By including the packedinstruction set 109 in the instruction set of a general-purposeprocessor 102, along with associated circuitry to execute theinstructions, the operations used by many multimedia applications may beperformed using packed data in a general-purpose processor 102. Thus,many multimedia applications can be accelerated and executed moreefficiently by using the full width of a processor's data bus forperforming operations on packed data. This can eliminate the need totransfer smaller units of data across the processor's data bus toperform one or more operations one data element at a time.

Alternate embodiments of an execution unit 108 can also be used in microcontrollers, embedded processors, graphics devices, DSPs, and othertypes of logic circuits. System 100 includes a memory 120. Memory 120can be a dynamic random access memory (DRAM) device, a static randomaccess memory (SRAM) device, flash memory device, or other memorydevice. Memory 120 can store instructions and/or data represented bydata signals that can be executed by the processor 102.

A system logic chip 116 is coupled to the processor bus 110 and memory120. The system logic chip 116 in the illustrated embodiment is a memorycontroller hub (MCH). The processor 102 can communicate to the MCH 116via a processor bus 110. The MCH 116 provides a high bandwidth memorypath 118 to memory 120 for instruction and data storage and for storageof graphics commands, data and textures. The MCH 116 is to direct datasignals between the processor 102, memory 120, and other components inthe system 100 and to bridge the data signals between processor bus 110,memory 120, and system I/O 122. In some embodiments, the system logicchip 116 can provide a graphics port for coupling to a graphicscontroller 112. The MCH 116 is coupled to memory 120 through a memoryinterface 118. The graphics card 112 is coupled to the MCH 116 throughan Accelerated Graphics Port (AGP) interconnect 114.

System 100 uses a proprietary hub interface bus 122 to couple the MCH116 to the I/O controller hub (ICH) 130. The ICH 130 provides directconnections to some I/O devices via a local I/O bus. The local I/O busis a high-speed I/O bus for connecting peripherals to the memory 120,chipset, and processor 102. Some examples are the audio controller,firmware hub (flash BIOS) 128, wireless transceiver 126, data storage124, legacy I/O controller containing user input and keyboardinterfaces, a serial expansion port such as Universal Serial Bus (USB),and a network controller 134. The data storage device 124 can comprise ahard disk drive, a floppy disk drive, a CD-ROM device, a flash memorydevice, or other mass storage device.

For another embodiment of a system, an instruction in accordance withone embodiment can be used with a system on a chip. One embodiment of asystem on a chip comprises of a processor and a memory. The memory forone such system is a flash memory. The flash memory can be located onthe same die as the processor and other system components. Additionally,other logic blocks such as a memory controller or graphics controllercan also be located on a system on a chip.

FIG. 1B illustrates a data processing system 140 which implements theprinciples of one embodiment of the present invention. It will bereadily appreciated by one of skill in the art that the embodimentsdescribed herein can be used with alternative processing systems withoutdeparture from the scope of embodiments of the invention.

Computer system 140 comprises a processing core 159 capable ofperforming at least one instruction in accordance with one embodiment.For one embodiment, processing core 159 represents a processing unit ofany type of architecture, including but not limited to a CISC, a RISC ora VLIW type architecture. Processing core 159 may also be suitable formanufacture in one or more process technologies and by being representedon a machine readable media in sufficient detail, may be suitable tofacilitate said manufacture.

Processing core 159 comprises an execution unit 142, a set of registerfile(s) 145, and a decoder 144. Processing core 159 also includesadditional circuitry (not shown) which is not necessary to theunderstanding of embodiments of the present invention. Execution unit142 is used for executing instructions received by processing core 159.In addition to performing typical processor instructions, execution unit142 can perform instructions in packed instruction set 143 forperforming operations on packed data formats. Packed instruction set 143includes instructions for performing embodiments of the invention andother packed instructions. Execution unit 142 is coupled to registerfile 145 by an internal bus. Register file 145 represents a storage areaon processing core 159 for storing information, including data. Aspreviously mentioned, it is understood that the storage area used forstoring the packed data is not critical. Execution unit 142 is coupledto decoder 144. Decoder 144 is used for decoding instructions receivedby processing core 159 into control signals and/or microcode entrypoints. In response to these control signals and/or microcode entrypoints, execution unit 142 performs the appropriate operations. In oneembodiment, the decoder is used to interpret the opcode of theinstruction, which will indicate what operation should be performed onthe corresponding data indicated within the instruction.

Processing core 159 is coupled with bus 141 for communicating withvarious other system devices, which may include but are not limited to,for example, synchronous dynamic random access memory (SDRAM) control146, static random access memory (SRAM) control 147, burst flash memoryinterface 148, personal computer memory card international association(PCMCIA)/compact flash (CF) card control 149, liquid crystal display(LCD) control 150, direct memory access (DMA) controller 151, andalternative bus master interface 152. In one embodiment, data processingsystem 140 may also comprise an I/O bridge 154 for communicating withvarious I/O devices via an I/O bus 153. Such I/O devices may include butare not limited to, for example, universal asynchronousreceiver/transmitter (UART) 155, universal serial bus (USB) 156,Bluetooth wireless UART 157 and I/O expansion interface 158.

One embodiment of data processing system 140 provides for mobile,network and/or wireless communications and a processing core 159 capableof performing SIMD operations including extended vector suffixcomparisons for Boyer-Moore searches. Processing core 159 may beprogrammed with various audio, video, imaging and communicationsalgorithms including discrete transformations such as a Walsh-Hadamardtransform, a fast Fourier transform (FFT), a discrete cosine transform(DCT), and their respective inverse transforms;compression/decompression techniques such as color space transformation,video encode motion estimation or video decode motion compensation; andmodulation/demodulation (MODEM) functions such as pulse coded modulation(PCM).

FIG. 1C illustrates another alternative embodiments of a data processingsystem capable of executing instructions to provide extended vectorsuffix comparisons for Boyer-Moore searches. In accordance with onealternative embodiment, data processing system 160 may include a mainprocessor 166, a SIMD coprocessor 161, a cache memory 167, and aninput/output system 168. The input/output system 168 may optionally becoupled to a wireless interface 169. SIMD coprocessor 161 is capable ofperforming operations including instructions in accordance with oneembodiment. Processing core 170 may be suitable for manufacture in oneor more process technologies and by being represented on a machinereadable media in sufficient detail, may be suitable to facilitate themanufacture of all or part of data processing system 160 includingprocessing core 170.

For one embodiment, SIMD coprocessor 161 comprises an execution unit 162and a set of register file(s) 164. One embodiment of main processor 166comprises a decoder 165 to recognize instructions of instruction set 163including instructions in accordance with one embodiment for executionby execution unit 162. For alternative embodiments, SIMD coprocessor 161also comprises at least part of decoder 165B to decode instructions ofinstruction set 163. Processing core 170 also includes additionalcircuitry (not shown) which is not necessary to the understanding ofembodiments of the present invention.

In operation, the main processor 166 executes a stream of dataprocessing instructions that control data processing operations of ageneral type including interactions with the cache memory 167, and theinput/output system 168. Embedded within the stream of data processinginstructions are SIMD coprocessor instructions. The decoder 165 of mainprocessor 166 recognizes these SIMD coprocessor instructions as being ofa type that should be executed by an attached SIMD coprocessor 161.Accordingly, the main processor 166 issues these SIMD coprocessorinstructions (or control signals representing SIMD coprocessorinstructions) on the coprocessor bus 171 where from they are received byany attached SIMD coprocessors. In this case, the SIMD coprocessor 161will accept and execute any received SIMD coprocessor instructionsintended for it.

Data may be received via wireless interface 169 for processing by theSIMD coprocessor instructions. For one example, voice communication maybe received in the form of a digital signal, which may be processed bythe SIMD coprocessor instructions to regenerate digital audio samplesrepresentative of the voice communications. For another example,compressed audio and/or video may be received in the form of a digitalbit stream, which may be processed by the SIMD coprocessor instructionsto regenerate digital audio samples and/or motion video frames. For oneembodiment of processing core 170, main processor 166, and a SIMDcoprocessor 161 are integrated into a single processing core 170comprising an execution unit 162, a set of register file(s) 164, and adecoder 165 to recognize instructions of instruction set 163 includinginstructions in accordance with one embodiment.

FIG. 2 is a block diagram of the micro-architecture for a processor 200that includes logic circuits to perform instructions in accordance withone embodiment of the present invention. In some embodiments, aninstruction in accordance with one embodiment can be implemented tooperate on data elements having sizes of byte, word, doubleword,quadword, etc., as well as datatypes, such as single and doubleprecision integer and floating point datatypes. In one embodiment thein-order front end 201 is the part of the processor 200 that fetchesinstructions to be executed and prepares them to be used later in theprocessor pipeline. The front end 201 may include several units. In oneembodiment, the instruction prefetcher 226 fetches instructions frommemory and feeds them to an instruction decoder 228 which in turndecodes or interprets them. For example, in one embodiment, the decoderdecodes a received instruction into one or more operations called“micro-instructions” or “micro-operations” (also called micro op oruops) that the machine can execute. In other embodiments, the decoderparses the instruction into an opcode and corresponding data and controlfields that are used by the micro-architecture to perform operations inaccordance with one embodiment. In one embodiment, the trace cache 230takes decoded uops and assembles them into program ordered sequences ortraces in the uop queue 234 for execution. When the trace cache 230encounters a complex instruction, the microcode ROM 232 provides theuops needed to complete the operation.

Some instructions are converted into a single micro-op, whereas othersneed several micro-ops to complete the full operation. In oneembodiment, if more than four micro-ops are needed to complete ainstruction, the decoder 228 accesses the microcode ROM 232 to do theinstruction. For one embodiment, an instruction can be decoded into asmall number of micro ops for processing at the instruction decoder 228.In another embodiment, an instruction can be stored within the microcodeROM 232 should a number of micro-ops be needed to accomplish theoperation. The trace cache 230 refers to a entry point programmablelogic array (PLA) to determine a correct micro-instruction pointer forreading the micro-code sequences to complete one or more instructions inaccordance with one embodiment from the micro-code ROM 232. After themicrocode ROM 232 finishes sequencing micro-ops for an instruction, thefront end 201 of the machine resumes fetching micro-ops from the tracecache 230.

The out-of-order execution engine 203 is where the instructions areprepared for execution. The out-of-order execution logic has a number ofbuffers to smooth out and reorder the flow of instructions to optimizeperformance as they go down the pipeline and get scheduled forexecution. The allocator logic allocates the machine buffers andresources that each uop needs in order to execute. The register renaminglogic renames logic registers onto entries in a register file. Theallocator also allocates an entry for each uop in one of the two uopqueues, one for memory operations and one for non-memory operations, infront of the instruction schedulers: memory scheduler, fast scheduler202, slow/general floating point scheduler 204, and simple floatingpoint scheduler 206. The uop schedulers 202, 204, 206, determine when auop is ready to execute based on the readiness of their dependent inputregister operand sources and the availability of the execution resourcesthe uops need to complete their operation. The fast scheduler 202 of oneembodiment can schedule on each half of the main clock cycle while theother schedulers can only schedule once per main processor clock cycle.The schedulers arbitrate for the dispatch ports to schedule uops forexecution.

Register files 208, 210, sit between the schedulers 202, 204, 206, andthe execution units 212, 214, 216, 218, 220, 222, 224 in the executionblock 211. There is a separate register file 208, 210, for integer andfloating point operations, respectively. Each register file 208, 210, ofone embodiment also includes a bypass network that can bypass or forwardjust completed results that have not yet been written into the registerfile to new dependent uops. The integer register file 208 and thefloating point register file 210 are also capable of communicating datawith the other. For one embodiment, the integer register file 208 issplit into two separate register files, one register file for the loworder 32 bits of data and a second register file for the high order 32bits of data. The floating point register file 210 of one embodiment has128 bit wide entries because floating point instructions typically haveoperands from 64 to 128 bits in width.

The execution block 211 contains the execution units 212, 214, 216, 218,220, 222, 224, where the instructions are actually executed. Thissection includes the register files 208, 210, that store the integer andfloating point data operand values that the micro-instructions need toexecute. The processor 200 of one embodiment is comprised of a number ofexecution units: address generation unit (AGU) 212, AGU 214, fast ALU216, fast ALU 218, slow ALU 220, floating point ALU 222, floating pointmove unit 224. For one embodiment, the floating point execution blocks222, 224, execute floating point, MMX, SIMD, and SSE, or otheroperations. The floating point ALU 222 of one embodiment includes a 64bit by 64 bit floating point divider to execute divide, square root, andremainder micro-ops. For embodiments of the present invention,instructions involving a floating point value may be handled with thefloating point hardware. In one embodiment, the ALU operations go to thehigh-speed ALU execution units 216, 218. The fast ALUs 216, 218, of oneembodiment can execute fast operations with an effective latency of halfa clock cycle. For one embodiment, most complex integer operations go tothe slow ALU 220 as the slow ALU 220 includes integer execution hardwarefor long latency type of operations, such as a multiplier, shifts, flaglogic, and branch processing. Memory load/store operations are executedby the AGUs 212, 214. For one embodiment, the integer ALUs 216, 218,220, are described in the context of performing integer operations on 64bit data operands. In alternative embodiments, the ALUs 216, 218, 220,can be implemented to support a variety of data bits including 16, 32,128, 256, etc. Similarly, the floating point units 222, 224, can beimplemented to support a range of operands having bits of variouswidths. For one embodiment, the floating point units 222, 224, canoperate on 128 bits wide packed data operands in conjunction with SIMDand multimedia instructions.

In one embodiment, the uops schedulers 202, 204, 206, dispatch dependentoperations before the parent load has finished executing. As uops arespeculatively scheduled and executed in processor 200, the processor 200also includes logic to handle memory misses. If a data load misses inthe data cache, there can be dependent operations in flight in thepipeline that have left the scheduler with temporarily incorrect data. Areplay mechanism tracks and re-executes instructions that use incorrectdata. Only the dependent operations need to be replayed and theindependent ones are allowed to complete. The schedulers and replaymechanism of one embodiment of a processor are also designed to catchinstructions that provide conversions between a mask register and ageneral purpose register.

The term “registers” may refer to the on-board processor storagelocations that are used as part of instructions to identify operands. Inother words, registers may be those that are usable from the outside ofthe processor (from a programmer's perspective). However, the registersof an embodiment should not be limited in meaning to a particular typeof circuit. Rather, a register of an embodiment is capable of storingand providing data, and performing the functions described herein. Theregisters described herein can be implemented by circuitry within aprocessor using any number of different techniques, such as dedicatedphysical registers, dynamically allocated physical registers usingregister renaming, combinations of dedicated and dynamically allocatedphysical registers, etc. In one embodiment, integer registers storethirty-two bit integer data. A register file of one embodiment alsocontains eight multimedia SIMD registers for packed data. For thediscussions below, the registers are understood to be data registersdesigned to hold packed data, such as 64 bits wide MMX™ registers (alsoreferred to as ‘mm’ registers in some instances) in microprocessorsenabled with MMX technology from Intel Corporation of Santa Clara,Calif. These MMX registers, available in both integer and floating pointforms, can operate with packed data elements that accompany SIMD and SSEinstructions. Similarly, 128 bits wide XMM registers relating to SSE2,SSE3, SSE4, or beyond (referred to generically as “SSEx”) technology canalso be used to hold such packed data operands. In one embodiment, instoring packed data and integer data, the registers do not need todifferentiate between the two data types. In one embodiment, integer andfloating point are either contained in the same register file ordifferent register files. Furthermore, in one embodiment, floating pointand integer data may be stored in different registers or the sameregisters.

In the examples of the following figures, a number of data operands aredescribed. FIG. 3A illustrates various packed data type representationsin multimedia registers according to one embodiment of the presentinvention. FIG. 3A illustrates data types for a packed byte 310, apacked word 320, and a packed doubleword (dword) 330 for 128 bits wideoperands. The packed byte format 310 of this example is 128 bits longand contains sixteen packed byte data elements. A byte is defined hereas 8 bits of data. Information for each byte data element is stored inbit 7 through bit 0 for byte 0, bit 15 through bit 8 for byte 1, bit 23through bit 16 for byte 2, and finally bit 120 through bit 127 for byte15. Thus, all available bits are used in the register. This storagearrangement increases the storage efficiency of the processor. As well,with sixteen data elements accessed, one operation can now be performedon sixteen data elements in parallel.

Generally, a data element is an individual piece of data that is storedin a single register or memory location with other data elements of thesame length. In packed data sequences relating to SSEx technology, thenumber of data elements stored in a XMM register is 128 bits divided bythe length in bits of an individual data element. Similarly, in packeddata sequences relating to MMX and SSE technology, the number of dataelements stored in an MMX register is 64 bits divided by the length inbits of an individual data element. Although the data types illustratedin FIG. 3A are 128 bit long, embodiments of the present invention canalso operate with 64 bit wide, 256 bit wide, 512 bit wide, or othersized operands. The packed word format 320 of this example is 128 bitslong and contains eight packed word data elements. Each packed wordcontains sixteen bits of information. The packed doubleword format 330of FIG. 3A is 128 bits long and contains four packed doubleword dataelements. Each packed doubleword data element contains thirty two bitsof information. A packed quadword is 128 bits long and contains twopacked quad-word data elements.

FIG. 3B illustrates alternative in-register data storage formats. Eachpacked data can include more than one independent data element. Threepacked data formats are illustrated; packed half 341, packed single 342,and packed double 343. One embodiment of packed half 341, packed single342, and packed double 343 contain fixed-point data elements. For analternative embodiment one or more of packed half 341, packed single342, and packed double 343 may contain floating-point data elements. Onealternative embodiment of packed half 341 is one hundred twenty-eightbits long containing eight 16-bit data elements. One embodiment ofpacked single 342 is one hundred twenty-eight bits long and containsfour 32-bit data elements. One embodiment of packed double 343 is onehundred twenty-eight bits long and contains two 64-bit data elements. Itwill be appreciated that such packed data formats may be furtherextended to other register lengths, for example, to 96-bits, 160-bits,192-bits, 224-bits, 256-bits, 512-bits or more.

FIG. 3C illustrates various signed and unsigned packed data typerepresentations in multimedia registers according to one embodiment ofthe present invention. Unsigned packed byte representation 344illustrates the storage of an unsigned packed byte in a SIMD register.Information for each byte data element is stored in bit seven throughbit zero for byte zero, bit fifteen through bit eight for byte one, bittwenty-three through bit sixteen for byte two, etc., and finally bit onehundred twenty through bit one hundred twenty-seven for byte fifteen.Thus, all available bits are used in the register. This storagearrangement can increase the storage efficiency of the processor. Aswell, with sixteen data elements accessed, one operation can now beperformed on sixteen data elements in a parallel fashion. Signed packedbyte representation 345 illustrates the storage of a signed packed byte.Note that the eighth bit of every byte data element is the signindicator. Unsigned packed word representation 346 illustrates how wordseven through word zero are stored in a SIMD register. Signed packedword representation 347 is similar to the unsigned packed wordin-register representation 346. Note that the sixteenth bit of each worddata element is the sign indicator. Unsigned packed doublewordrepresentation 348 shows how doubleword data elements are stored. Signedpacked doubleword representation 349 is similar to unsigned packeddoubleword in-register representation 348. Note that the necessary signbit is the thirty-second bit of each doubleword data element.

FIG. 3D is a depiction of one embodiment of an operation encoding(opcode) format 360, having thirty-two or more bits, and register/memoryoperand addressing modes corresponding with a type of opcode formatdescribed in the “Intel® 64 and IA-32 Intel Architecture SoftwareDeveloper's Manual Combined Volumes 2A and 2B: Instruction Set ReferenceA-Z,” which is which is available from Intel Corporation, Santa Clara,Calif. on the world-wide-web (www) atintel.com/products/processor/manuals/. In one embodiment, andinstruction may be encoded by one or more of fields 361 and 362. Up totwo operand locations per instruction may be identified, including up totwo source operand identifiers 364 and 365. For one embodiment,destination operand identifier 366 is the same as source operandidentifier 364, whereas in other embodiments they are different. For analternative embodiment, destination operand identifier 366 is the sameas source operand identifier 365, whereas in other embodiments they aredifferent. In one embodiment, one of the source operands identified bysource operand identifiers 364 and 365 is overwritten by the results ofthe instruction, whereas in other embodiments identifier 364 correspondsto a source register element and identifier 365 corresponds to adestination register element. For one embodiment, operand identifiers364 and 365 may be used to identify 32-bit or 64-bit source anddestination operands.

FIG. 3E is a depiction of another alternative operation encoding(opcode) format 370, having forty or more bits. Opcode format 370corresponds with opcode format 360 and comprises an optional prefix byte378. An instruction according to one embodiment may be encoded by one ormore of fields 378, 371, and 372. Up to two operand locations perinstruction may be identified by source operand identifiers 374 and 375and by prefix byte 378. For one embodiment, prefix byte 378 may be usedto identify 32-bit or 64-bit source and destination operands. For oneembodiment, destination operand identifier 376 is the same as sourceoperand identifier 374, whereas in other embodiments they are different.For an alternative embodiment, destination operand identifier 376 is thesame as source operand identifier 375, whereas in other embodiments theyare different. In one embodiment, an instruction operates on one or moreof the operands identified by operand identifiers 374 and 375 and one ormore operands identified by the operand identifiers 374 and 375 isoverwritten by the results of the instruction, whereas in otherembodiments, operands identified by identifiers 374 and 375 are writtento another data element in another register. Opcode formats 360 and 370allow register to register, memory to register, register by memory,register by register, register by immediate, register to memoryaddressing specified in part by MOD fields 363 and 373 and by optionalscale-index-base and displacement bytes.

Turning next to FIG. 3F, in some alternative embodiments, 64-bit (or128-bit, or 256-bit, or 512-bit or more) single instruction multipledata (SIMD) arithmetic operations may be performed through a coprocessordata processing (CDP) instruction. Operation encoding (opcode) format380 depicts one such CDP instruction having CDP opcode fields 382 and389. The type of CDP instruction, for alternative embodiments,operations may be encoded by one or more of fields 383, 384, 387, and388. Up to three operand locations per instruction may be identified,including up to two source operand identifiers 385 and 390 and onedestination operand identifier 386. One embodiment of the coprocessorcan operate on 8, 16, 32, and 64 bit values. For one embodiment, aninstruction is performed on integer data elements. In some embodiments,an instruction may be executed conditionally, using condition field 381.For some embodiments, source data sizes may be encoded by field 383.

In some embodiments, Zero (Z), negative (N), carry (C), and overflow (V)detection can be done on SIMD fields. For some instructions, the type ofsaturation may be encoded by field 384.

Various SIMD instructions may be utilized as vector comparisons inBoyer-Moore string searches. For instance, some processors may supportstreaming SIMD Extension 4 (SSE4) instructions, including SSE4.2instructions. SSE4.2 instructions may perform character searches andcomparisons on two operands of a particular number of bytes (e.g., 16)at a time. One example is PCMPESTRI, or “Packed Compare Explicit LengthStrings.” This operation, which is an ordered comparison, may return anindex within a data buffer (e.g., a sliding window) at which a potentialpattern match begins. For example, a PCMPESTRI operation provided with asearch pattern “GABCD” and a data buffer “ERGTYHABCDRGABCD” may returnan index of 11, and thus may be useful in vector suffix comparisons forBoyer-Moore searches.

Turning next to FIG. 3G is a depiction of another alternative operationencoding (opcode) format 397, to provide extended vector suffixcomparisons for Boyer-Moore searches according to another embodiment,corresponding with a type of opcode format described in the “Intel®Advanced Vector Extensions Programming Reference,” which is availablefrom Intel Corp., Santa Clara, Calif. on the world-wide-web (www) atintel.com/products/processor/manuals/.

The original x86 instruction set provided for a 1-byte opcode withvarious formats of address syllable and immediate operand contained inadditional bytes whose presence was known from the first “opcode” byte.Additionally, there were certain byte values that were reserved asmodifiers to the opcode (called prefixes, as they had to be placedbefore the instruction). When the original palette of 256 opcode bytes(including these special prefix values) was exhausted, a single byte wasdedicated as an escape to a new set of 256 opcodes. As vectorinstructions (e.g., SIMD) were added, a need for more opcodes wasgenerated, and the “two byte” opcode map also was insufficient, evenwhen expanded through the use of prefixes. To this end, new instructionswere added in additional maps which use 2 bytes plus an optional prefixas an identifier.

Additionally, in order to facilitate additional registers in 64-bitmode, an additional prefix may be used (called “REX”) in between theprefixes and the opcode (and any escape bytes necessary to determine theopcode). In one embodiment, the REX may have 4 “payload” bits toindicate use of additional registers in 64-bit mode. In otherembodiments it may have fewer or more than 4 bits. The general format ofat least one instruction set (which corresponds generally with format360 and/or format 370) is illustrated generically by the following:

-   -   [prefixes] [rex] escape [escape2] opcode modrm (etc.)

Opcode format 397 corresponds with opcode format 370 and comprisesoptional VEX prefix bytes 391 (beginning with C4 hex or C5 hex in oneembodiment) to replace most other commonly used legacy instructionprefix bytes and escape codes. For example, the following illustrates anembodiment using two fields to encode an instruction, which may be usedwhen a second escape code is not present in the original instruction. Inthe embodiment illustrated below, legacy escape is represented by a newescape value, legacy prefixes are fully compressed as part of the“payload” bytes, legacy prefixes are reclaimed and available for futureexpansion, and new features are added (e.g., increased vector length andan additional source register specifier).

When a second escape code is present in the original instruction, orwhen extra bits (e.g, the XB and W fields) in the REX field need to beused. In the alternative embodiment illustrated below, the first legacyescape and legacy prefixes are compressed similar to the above, and thesecond escape code is compressed in a “map” field, with future map orfeature space available, and again, new features are added (e.g.,increased vector length and an additional source register specifier).

An instruction according to one embodiment may be encoded by one or moreof fields 391 and 392. Up to four operand locations per instruction maybe identified by field 391 in combination with source operandidentifiers 374 and 375 and in combination with an optionalscale-index-base (SIB) identifier 393, an optional displacementidentifier 394, and an optional immediate byte 395. For one embodiment,VEX prefix bytes 391 may be used to identify 32-bit or 64-bit source anddestination operands and/or 128-bit or 256-bit SIMD register or memoryoperands. For one embodiment, the functionality provided by opcodeformat 397 may be redundant with opcode format 370, whereas in otherembodiments they are different. Opcode formats 370 and 397 allowregister to register, memory to register, register by memory, registerby register, register by immediate, register to memory addressingspecified in part by MOD field 373 and by optional (SIB) identifier 393,an optional displacement identifier 394, and an optional immediate byte395.

Turning next to FIG. 3H is a depiction of another alternative operationencoding (opcode) format 398, to provide extended vector suffixcomparisons for Boyer-Moore searches according to another embodiment.Opcode format 398 corresponds with opcode formats 370 and 397 andcomprises optional EVEX prefix bytes 396 (beginning with 62 hex in oneembodiment) to replace most other commonly used legacy instructionprefix bytes and escape codes and provide additional functionality. Aninstruction according to one embodiment may be encoded by one or more offields 396 and 392. Up to four operand locations per instruction and amask may be identified by field 396 in combination with source operandidentifiers 374 and 375 and in combination with an optionalscale-index-base (SIB) identifier 393, an optional displacementidentifier 394, and an optional immediate byte 395. For one embodiment,EVEX prefix bytes 396 may be used to identify 32-bit or 64-bit sourceand destination operands and/or 128-bit, 256-bit or 512-bit SIMDregister or memory operands. For one embodiment, the functionalityprovided by opcode format 398 may be redundant with opcode formats 370or 397, whereas in other embodiments they are different. Opcode format398 allows register to register, memory to register, register by memory,register by register, register by immediate, register to memoryaddressing, with masks, specified in part by MOD field 373 and byoptional (SIB) identifier 393, an optional displacement identifier 394,and an optional immediate byte 395. The general format of at least oneinstruction set (which corresponds generally with format 360 and/orformat 370) is illustrated generically by the following:

-   -   evex1 RXBmmmmm WvvvLpp evex4 opcode modrm [sib] [disp] [imm].

For one embodiment an instruction encoded according to the EVEX format398 may have additional “payload” bits that may be used to provideconversions between a mask register and a general purpose register withadditional new features such as, for example, a user configurable maskregister, or an additional operand, or selections from among 128-bit,256-bit or 512-bit vector registers, or more registers from which toselect, etc.

For example, VEX format 397 or EVEX format 398 may be used to provideextended vector suffix comparisons for Boyer-Moore searches.Additionally, where VEX format 397 or EVEX format 398 may be used toprovide extended vector suffix comparisons for Boyer-Moore searches for128-bit, 256-bit, 512-bit or larger (or smaller) vector registers.

Example instructions to provide extended vector suffix comparisons forBoyer-Moore searches are illustrated by the following examples:

Instruction source1 source2 source3 source4 description fwd-rev comparexmm1 xmm2 Imm8 Compare (equal ordered) forward mem128 and reversedstring suffixes of a pattern in xmm1 with a target string in xmm2 or ina 128-bit memory operand to generate a mask or index according to theimmediate byte, Imm8. two-fwd compare xmm1 ymm1 Imm8 Compare (equalordered) two mem256 forward string suffixes of a target string in ymm2or in a 256-bit memory operand with a pattern in xmm1 to generate a maskor index according to the immediate byte, Imm8. four-fwd compare xmm1zmm1 Imm8 Compare (equal ordered) four mem512 forward string suffixes ofa target string in zmm1 or in a 512-bit memory operand with a pattern inxmm1 to generate a mask or index according to the immediate byte, Imm8.fwd-rev compare xmm1 zmm1 Imm8 Compare (equal ordered) forward mem512and reversed string suffixes of a pattern in xmm1 with a target stringin zmm1 or a 512-bit memory operand to generate a mask or indexaccording to the immediate byte, Imm8. two-fwd compare xmm1 xmm2 Imm8xmm3 Compare (equal ordered) two mem128 forward string suffixes of atarget string in xmm2 and in xmm3 or a 128-bit memory operand with apattern in xmm1 to generate a mask or index according to the immediatebyte, Imm8.

For some embodiments of an extended vector suffix comparison instructioninvolving two forward equal ordered suffix comparisons of an m-elementpattern with a 2m-element target string, a mask or index may begenerated for up to 2m element positions in the target string. For someembodiments of an extended vector suffix comparison instructioninvolving a forward and a reversed equal ordered suffix comparison of anm-element pattern with an m-element suffix of a target string, a mask orindex may be generated according to an immediate byte, for up to 2m−1element positions in the target string. For some alternative embodimentsof a forward and a reversed equal ordered suffix comparison using anadditional target string operand, a mask or index may be generated forup to 2m element positions in the target string. For some embodimentsthe underlying implementation may include specialized hardware toperform the forward and a reversed equal ordered suffix comparisons orthe two forward equal ordered suffix comparisons in parallel. For somealternative embodiments the underlying implementation may includemicrocode sequences to support extended vector suffix comparisoninstructions.

FIG. 4A is a block diagram illustrating an in-order pipeline and aregister renaming stage, out-of-order issue/execution pipeline accordingto at least one embodiment of the invention. FIG. 4B is a block diagramillustrating an in-order architecture core and a register renaminglogic, out-of-order issue/execution logic to be included in a processoraccording to at least one embodiment of the invention. The solid linedboxes in FIG. 4A illustrate the in-order pipeline, while the dashedlined boxes illustrates the register renaming, out-of-orderissue/execution pipeline. Similarly, the solid lined boxes in FIG. 4Billustrate the in-order architecture logic, while the dashed lined boxesillustrates the register renaming logic and out-of-order issue/executionlogic.

In FIG. 4A, a processor pipeline 400 includes a fetch stage 402, alength decode stage 404, a decode stage 406, an allocation stage 408, arenaming stage 410, a scheduling (also known as a dispatch or issue)stage 412, a register read/memory read stage 414, an execute stage 416,a write back/memory write stage 418, an exception handling stage 422,and a commit stage 424.

In FIG. 4B, arrows denote a coupling between two or more units and thedirection of the arrow indicates a direction of data flow between thoseunits. FIG. 4B shows processor core 490 including a front end unit 430coupled to an execution engine unit 450, and both are coupled to amemory unit 470.

The core 490 may be a reduced instruction set computing (RISC) core, acomplex instruction set computing (CISC) core, a very long instructionword (VLIW) core, or a hybrid or alternative core type. As yet anotheroption, the core 490 may be a special-purpose core, such as, forexample, a network or communication core, compression engine, graphicscore, or the like.

The front end unit 430 includes a branch prediction unit 432 coupled toan instruction cache unit 434, which is coupled to an instructiontranslation lookaside buffer (TLB) 436, which is coupled to aninstruction fetch unit 438, which is coupled to a decode unit 440. Thedecode unit or decoder may decode instructions, and generate as anoutput one or more micro-operations, micro-code entry points,microinstructions, other instructions, or other control signals, whichare decoded from, or which otherwise reflect, or are derived from, theoriginal instructions. The decoder may be implemented using variousdifferent mechanisms. Examples of suitable mechanisms include, but arenot limited to, look-up tables, hardware implementations, programmablelogic arrays (PLAs), microcode read only memories (ROMs), etc. Theinstruction cache unit 434 is further coupled to a level 2 (L2) cacheunit 476 in the memory unit 470. The decode unit 440 is coupled to arename/allocator unit 452 in the execution engine unit 450.

The execution engine unit 450 includes the rename/allocator unit 452coupled to a retirement unit 454 and a set of one or more schedulerunit(s) 456. The scheduler unit(s) 456 represents any number ofdifferent schedulers, including reservations stations, centralinstruction window, etc. The scheduler unit(s) 456 is coupled to thephysical register file(s) unit(s) 458. Each of the physical registerfile(s) units 458 represents one or more physical register files,different ones of which store one or more different data types, such asscalar integer, scalar floating point, packed integer, packed floatingpoint, vector integer, vector floating point, etc., status (e.g., aninstruction pointer that is the address of the next instruction to beexecuted), etc. The physical register file(s) unit(s) 458 is overlappedby the retirement unit 454 to illustrate various ways in which registerrenaming and out-of-order execution may be implemented (e.g., using areorder buffer(s) and a retirement register file(s), using a futurefile(s), a history buffer(s), and a retirement register file(s); using aregister maps and a pool of registers; etc.). Generally, thearchitectural registers are visible from the outside of the processor orfrom a programmer's perspective. The registers are not limited to anyknown particular type of circuit. Various different types of registersare suitable as long as they are capable of storing and providing dataas described herein. Examples of suitable registers include, but are notlimited to, dedicated physical registers, dynamically allocated physicalregisters using register renaming, combinations of dedicated anddynamically allocated physical registers, etc. The retirement unit 454and the physical register file(s) unit(s) 458 are coupled to theexecution cluster(s) 460. The execution cluster(s) 460 includes a set ofone or more execution units 462 and a set of one or more memory accessunits 464. The execution units 462 may perform various operations (e.g.,shifts, addition, subtraction, multiplication) and on various types ofdata (e.g., scalar floating point, packed integer, packed floatingpoint, vector integer, vector floating point). While some embodimentsmay include a number of execution units dedicated to specific functionsor sets of functions, other embodiments may include only one executionunit or multiple execution units that all perform all functions. Thescheduler unit(s) 456, physical register file(s) unit(s) 458, andexecution cluster(s) 460 are shown as being possibly plural becausecertain embodiments create separate pipelines for certain types ofdata/operations (e.g., a scalar integer pipeline, a scalar floatingpoint/packed integer/packed floating point/vector integer/vectorfloating point pipeline, and/or a memory access pipeline that each havetheir own scheduler unit, physical register file(s) unit, and/orexecution cluster, and in the case of a separate memory access pipeline,certain embodiments are implemented in which only the execution clusterof this pipeline has the memory access unit(s) 464). It should also beunderstood that where separate pipelines are used, one or more of thesepipelines may be out-of-order issue/execution and the rest in-order.

The set of memory access units 464 is coupled to the memory unit 470,which includes a data TLB unit 472 coupled to a data cache unit 474coupled to a level 2 (L2) cache unit 476. In one exemplary embodiment,the memory access units 464 may include a load unit, a store addressunit, and a store data unit, each of which is coupled to the data TLBunit 472 in the memory unit 470. The L2 cache unit 476 is coupled to oneor more other levels of cache and eventually to a main memory.

By way of example, the exemplary register renaming, out-of-orderissue/execution core architecture may implement the pipeline 400 asfollows: 1) the instruction fetch 438 performs the fetch and lengthdecoding stages 402 and 404; 2) the decode unit 440 performs the decodestage 406; 3) the rename/allocator unit 452 performs the allocationstage 408 and renaming stage 410; 4) the scheduler unit(s) 456 performsthe schedule stage 412; 5) the physical register file(s) unit(s) 458 andthe memory unit 470 perform the register read/memory read stage 414; theexecution cluster 460 perform the execute stage 416; 6) the memory unit470 and the physical register file(s) unit(s) 458 perform the writeback/memory write stage 418; 7) various units may be involved in theexception handling stage 422; and 8) the retirement unit 454 and thephysical register file(s) unit(s) 458 perform the commit stage 424.

The core 490 may support one or more instructions sets (e.g., the x86instruction set (with some extensions that have been added with newerversions); the MIPS instruction set of MIPS Technologies of Sunnyvale,Calif.; the ARM instruction set (with optional additional extensionssuch as NEON) of ARM Holdings of Sunnyvale, Calif.).

It should be understood that the core may support multithreading(executing two or more parallel sets of operations or threads), and maydo so in a variety of ways including time sliced multithreading,simultaneous multithreading (where a single physical core provides alogical core for each of the threads that physical core issimultaneously multithreading), or a combination thereof (e.g., timesliced fetching and decoding and simultaneous multithreading thereaftersuch as in the Intel® Hyperthreading technology).

While register renaming is described in the context of out-of-orderexecution, it should be understood that register renaming may be used inan in-order architecture. While the illustrated embodiment of theprocessor also includes a separate instruction and data cache units434/474 and a shared L2 cache unit 476, alternative embodiments may havea single internal cache for both instructions and data, such as, forexample, a Level 1 (L1) internal cache, or multiple levels of internalcache. In some embodiments, the system may include a combination of aninternal cache and an external cache that is external to the core and/orthe processor. Alternatively, all of the cache may be external to thecore and/or the processor.

FIG. 5 is a block diagram of a single core processor and a multicoreprocessor 500 with integrated memory controller and graphics accordingto embodiments of the invention. The solid lined boxes in FIG. 5illustrate a processor 500 with a single core 502A, a system agent 510,a set of one or more bus controller units 516, while the optionaladdition of the dashed lined boxes illustrates an alternative processor500 with multiple cores 502A-N, a set of one or more integrated memorycontroller unit(s) 514 in the system agent unit 510, and an integratedgraphics logic 508.

The memory hierarchy includes one or more levels of cache within thecores, a set or one or more shared cache units 506, and external memory(not shown) coupled to the set of integrated memory controller units514. The set of shared cache units 506 may include one or more mid-levelcaches, such as level 2 (L2), level 3 (L3), level 4 (L4), or otherlevels of cache, a last level cache (LLC), and/or combinations thereof.While in one embodiment a ring based interconnect unit 512 interconnectsthe integrated graphics logic 508, the set of shared cache units 506,and the system agent unit 510, alternative embodiments may use anynumber of well-known techniques for interconnecting such units.

In some embodiments, one or more of the cores 502A-N are capable ofmultithreading. The system agent 510 includes those componentscoordinating and operating cores 502A-N. The system agent unit 510 mayinclude for example a power control unit (PCU) and a display unit. ThePCU may be or include logic and components needed for regulating thepower state of the cores 502A-N and the integrated graphics logic 508.The display unit is for driving one or more externally connecteddisplays.

The cores 502A-N may be homogenous or heterogeneous in terms ofarchitecture and/or instruction set. For example, some of the cores502A-N may be in order while others are out-of-order. As anotherexample, two or more of the cores 502A-N may be capable of execution thesame instruction set, while others may be capable of executing only asubset of that instruction set or a different instruction set.

The processor may be a general-purpose processor, such as a Core™ i3,i5, i7, 2 Duo and Quad, Xeon™, Itanium™, XScale™ or StrongARM™processor, which are available from Intel Corporation, of Santa Clara,Calif. Alternatively, the processor may be from another company, such asARM Holdings, Ltd, MIPS, etc. The processor may be a special-purposeprocessor, such as, for example, a network or communication processor,compression engine, graphics processor, co-processor, embeddedprocessor, or the like. The processor may be implemented on one or morechips. The processor 500 may be a part of and/or may be implemented onone or more substrates using any of a number of process technologies,such as, for example, BiCMOS, CMOS, or NMOS.

FIGS. 6-8 are exemplary systems suitable for including the processor500, while FIG. 9 is an exemplary system on a chip (SoC) that mayinclude one or more of the cores 502. Other system designs andconfigurations known in the arts for laptops, desktops, handheld PCs,personal digital assistants, engineering workstations, servers, networkdevices, network hubs, switches, embedded processors, digital signalprocessors (DSPs), graphics devices, video game devices, set-top boxes,micro controllers, cell phones, portable media players, hand helddevices, and various other electronic devices, are also suitable. Ingeneral, a huge variety of systems or electronic devices capable ofincorporating a processor and/or other execution logic as disclosedherein are generally suitable.

Referring now to FIG. 6, shown is a block diagram of a system 600 inaccordance with one embodiment of the present invention. The system 600may include one or more processors 610, 615, which are coupled tographics memory controller hub (GMCH) 620. The optional nature ofadditional processors 615 is denoted in FIG. 6 with broken lines.

Each processor 610,615 may be some version of the processor 500.However, it should be noted that it is unlikely that integrated graphicslogic and integrated memory control units would exist in the processors610,615. FIG. 6 illustrates that the GMCH 620 may be coupled to a memory640 that may be, for example, a dynamic random access memory (DRAM). TheDRAM may, for at least one embodiment, be associated with a non-volatilecache.

The GMCH 620 may be a chipset, or a portion of a chipset. The GMCH 620may communicate with the processor(s) 610, 615 and control interactionbetween the processor(s) 610, 615 and memory 640. The GMCH 620 may alsoact as an accelerated bus interface between the processor(s) 610, 615and other elements of the system 600. For at least one embodiment, theGMCH 620 communicates with the processor(s) 610, 615 via a multi-dropbus, such as a frontside bus (FSB) 695.

Furthermore, GMCH 620 is coupled to a display 645 (such as a flat paneldisplay). GMCH 620 may include an integrated graphics accelerator. GMCH620 is further coupled to an input/output (I/O) controller hub (ICH)650, which may be used to couple various peripheral devices to system600. Shown for example in the embodiment of FIG. 6 is an externalgraphics device 660, which may be a discrete graphics device coupled toICH 650, along with another peripheral device 670.

Alternatively, additional or different processors may also be present inthe system 600. For example, additional processor(s) 615 may includeadditional processors(s) that are the same as processor 610, additionalprocessor(s) that are heterogeneous or asymmetric to processor 610,accelerators (such as, e.g., graphics accelerators or digital signalprocessing (DSP) units), field programmable gate arrays, or any otherprocessor. There can be a variety of differences between the physicalresources 610, 615 in terms of a spectrum of metrics of merit includingarchitectural, micro-architectural, thermal, power consumptioncharacteristics, and the like. These differences may effectivelymanifest themselves as asymmetry and heterogeneity amongst theprocessors 610, 615. For at least one embodiment, the various processors610, 615 may reside in the same die package.

Referring now to FIG. 7, shown is a block diagram of a second system 700in accordance with an embodiment of the present invention. As shown inFIG. 7, multiprocessor system 700 is a point-to-point interconnectsystem, and includes a first processor 770 and a second processor 780coupled via a point-to-point interconnect 750. Each of processors 770and 780 may be some version of the processor 500 as one or more of theprocessors 610,615.

While shown with only two processors 770, 780, it is to be understoodthat the scope of the present invention is not so limited. In otherembodiments, one or more additional processors may be present in a givenprocessor.

Processors 770 and 780 are shown including integrated memory controllerunits 772 and 782, respectively. Processor 770 also includes as part ofits bus controller units point-to-point (P-P) interfaces 776 and 778;similarly, second processor 780 includes P-P interfaces 786 and 788.Processors 770, 780 may exchange information via a point-to-point (P-P)interface 750 using P-P interface circuits 778, 788. As shown in FIG. 7,IMCs 772 and 782 couple the processors to respective memories, namely amemory 732 and a memory 734, which may be portions of main memorylocally attached to the respective processors.

Processors 770, 780 may each exchange information with a chipset 790 viaindividual P-P interfaces 752, 754 using point to point interfacecircuits 776, 794, 786, 798. Chipset 790 may also exchange informationwith a high-performance graphics circuit 738 via a high-performancegraphics interface 739.

A shared cache (not shown) may be included in either processor oroutside of both processors, yet connected with the processors via P-Pinterconnect, such that either or both processors' local cacheinformation may be stored in the shared cache if a processor is placedinto a low power mode.

Chipset 790 may be coupled to a first bus 716 via an interface 796. Inone embodiment, first bus 716 may be a Peripheral Component Interconnect(PCI) bus, or a bus such as a PCI Express bus or another thirdgeneration I/O interconnect bus, although the scope of the presentinvention is not so limited.

As shown in FIG. 7, various I/O devices 714 may be coupled to first bus716, along with a bus bridge 718 which couples first bus 716 to a secondbus 720. In one embodiment, second bus 720 may be a low pin count (LPC)bus. Various devices may be coupled to second bus 720 including, forexample, a keyboard and/or mouse 722, communication devices 727 and astorage unit 728 such as a disk drive or other mass storage device whichmay include instructions/code and data 730, in one embodiment. Further,an audio I/O 724 may be coupled to second bus 720. Note that otherarchitectures are possible. For example, instead of the point-to-pointarchitecture of FIG. 7, a system may implement a multi-drop bus or othersuch architecture.

Referring now to FIG. 8, shown is a block diagram of a third system 800in accordance with an embodiment of the present invention. Like elementsin FIG. 7 and FIG. 8 bear like reference numerals, and certain aspectsof FIG. 7 have been omitted from FIG. 8 in order to avoid obscuringother aspects of FIG. 8.

FIG. 8 illustrates that the processors 870, 880 may include integratedmemory and I/O control logic (“CL”) 872 and 882, respectively. For atleast one embodiment, the CL 872, 882 may include integrated memorycontroller units such as that described above in connection with FIGS. 5and 7. In addition. CL 872, 882 may also include I/O control logic. FIG.8 illustrates that not only are the memories 832, 834 coupled to the CL872, 882, but also that I/O devices 814 are also coupled to the controllogic 872, 882. Legacy I/O devices 815 are coupled to the chipset 890.

Referring now to FIG. 9, shown is a block diagram of a SoC 900 inaccordance with an embodiment of the present invention. Similar elementsin FIG. 5 bear like reference numerals. Also, dashed lined boxes areoptional features on more advanced SoCs. In FIG. 9, an interconnectunit(s) 902 is coupled to: an application processor 910 which includes aset of one or more cores 502A-N and shared cache unit(s) 506; a systemagent unit 510; a bus controller unit(s) 516; an integrated memorycontroller unit(s) 514; a set of one or more media processors 920 whichmay include integrated graphics logic 508, an image processor 924 forproviding still and/or video camera functionality, an audio processor926 for providing hardware audio acceleration, and a video processor 928for providing video encode/decode acceleration; an static random accessmemory (SRAM) unit 930; a direct memory access (DMA) unit 932; and adisplay unit 940 for coupling to one or more external displays.

FIG. 10 illustrates a processor containing a central processing unit(CPU) and a graphics processing unit (GPU), which may perform at leastone instruction according to one embodiment. In one embodiment, aninstruction to perform operations according to at least one embodimentcould be performed by the CPU. In another embodiment, the instructioncould be performed by the GPU. In still another embodiment, theinstruction may be performed through a combination of operationsperformed by the GPU and the CPU. For example, in one embodiment, aninstruction in accordance with one embodiment may be received anddecoded for execution on the GPU. However, one or more operations withinthe decoded instruction may be performed by a CPU and the resultreturned to the GPU for final retirement of the instruction. Conversely,in some embodiments, the CPU may act as the primary processor and theGPU as the co-processor.

In some embodiments, instructions that benefit from highly parallel,throughput processors may be performed by the GPU, while instructionsthat benefit from the performance of processors that benefit from deeplypipelined architectures may be performed by the CPU. For example,graphics, scientific applications, financial applications and otherparallel workloads may benefit from the performance of the GPU and beexecuted accordingly, whereas more sequential applications, such asoperating system kernel or application code may be better suited for theCPU.

In FIG. 10, processor 1000 includes a CPU 1005, GPU 1010, imageprocessor 1015, video processor 1020, USB controller 1025, UARTcontroller 1030, SPI/SDIO controller 1035, display device 1040,High-Definition Multimedia Interface (HDMI) controller 1045, MIPIcontroller 1050, flash memory controller 1055, dual data rate (DDR)controller 1060, security engine 1065, and I²S/I²C (Integrated InterchipSound/Inter-Integrated Circuit) interface 1070. Other logic and circuitsmay be included in the processor of FIG. 10, including more CPUs or GPUsand other peripheral interface controllers.

One or more aspects of at least one embodiment may be implemented byrepresentative data stored on a machine-readable medium which representsvarious logic within the processor, which when read by a machine causesthe machine to fabricate logic to perform the techniques describedherein. Such representations, known as “IP cores” may be stored on atangible, machine readable medium (“tape”) and supplied to variouscustomers or manufacturing facilities to load into the fabricationmachines that actually make the logic or processor. For example, IPcores, such as the Cortex™ family of processors developed by ARMHoldings, Ltd. and Loongson IP cores developed the Institute ofComputing Technology (ICT) of the Chinese Academy of Sciences may belicensed or sold to various customers or licensees, such as TexasInstruments, Qualcomm, Apple, or Samsung and implemented in processorsproduced by these customers or licensees.

FIG. 11 shows a block diagram illustrating the development of IP coresaccording to one embodiment. Storage 1130 includes simulation software1120 and/or hardware or software model 1110. In one embodiment, the datarepresenting the IP core design can be provided to the storage 1130 viamemory 1140 (e.g., hard disk), wired connection (e.g., internet) 1150 orwireless connection 1160. The IP core information generated by thesimulation tool and model can then be transmitted to a fabricationfacility where it can be fabricated by a third party to perform at leastone instruction in accordance with at least one embodiment.

In some embodiments, one or more instructions may correspond to a firsttype or architecture (e.g., x86) and be translated or emulated on aprocessor of a different type or architecture (e.g., ARM). Aninstruction, according to one embodiment, may therefore be performed onany processor or processor type, including ARM, x86, MIPS, a GPU, orother processor type or architecture.

FIG. 12 illustrates how an instruction of a first type is emulated by aprocessor of a different type, according to one embodiment. In FIG. 12,program 1205 contains some instructions that may perform the same orsubstantially the same function as an instruction according to oneembodiment. However the instructions of program 1205 may be of a typeand/or format that is different or incompatible with processor 1215,meaning the instructions of the type in program 1205 may not be able tobe executed natively by the processor 1215. However, with the help ofemulation logic, 1210, the instructions of program 1205 are translatedinto instructions that are natively capable of being executed by theprocessor 1215. In one embodiment, the emulation logic is embodied inhardware. In another embodiment, the emulation logic is embodied in atangible, machine-readable medium containing software to translateinstructions of the type in the program 1205 into the type nativelyexecutable by the processor 1215. In other embodiments, emulation logicis a combination of fixed-function or programmable hardware and aprogram stored on a tangible, machine-readable medium. In oneembodiment, the processor contains the emulation logic, whereas in otherembodiments, the emulation logic exists outside of the processor and isprovided by a third party. In one embodiment, the processor is capableof loading the emulation logic embodied in a tangible, machine-readablemedium containing software by executing microcode or firmware containedin or associated with the processor.

FIG. 13 is a block diagram contrasting the use of a software instructionconverter to convert binary instructions in a source instruction set tobinary instructions in a target instruction set according to embodimentsof the invention. In the illustrated embodiment, the instructionconverter is a software instruction converter, although alternativelythe instruction converter may be implemented in software, firmware,hardware, or various combinations thereof. FIG. 13 shows a program in ahigh level language 1302 may be compiled using an x86 compiler 1304 togenerate x86 binary code 1306 that may be natively executed by aprocessor with at least one x86 instruction set core 1316. The processorwith at least one x86 instruction set core 1316 represents any processorthat can perform substantially the same functions as a Intel processorwith at least one x86 instruction set core by compatibly executing orotherwise processing (1) a substantial portion of the instruction set ofthe Intel x86 instruction set core or (2) object code versions ofapplications or other software targeted to run on an Intel processorwith at least one x86 instruction set core, in order to achievesubstantially the same result as an Intel processor with at least onex86 instruction set core. The x86 compiler 1304 represents a compilerthat is operable to generate x86 binary code 1306 (e.g., object code)that can, with or without additional linkage processing, be executed onthe processor with at least one x86 instruction set core 1316.Similarly, FIG. 13 shows the program in the high level language 1302 maybe compiled using an alternative instruction set compiler 1308 togenerate alternative instruction set binary code 1310 that may benatively executed by a processor without at least one x86 instructionset core 1314 (e.g., a processor with cores that execute the MIPSinstruction set of MIPS Technologies of Sunnyvale, Calif. and/or thatexecute the ARM instruction set of ARM Holdings of Sunnyvale, Calif.).The instruction converter 1312 is used to convert the x86 binary code1306 into code that may be natively executed by the processor without anx86 instruction set core 1314. This converted code is not likely to bethe same as the alternative instruction set binary code 1310 because aninstruction converter capable of this is difficult to make; however, theconverted code will accomplish the general operation and be made up ofinstructions from the alternative instruction set. Thus, the instructionconverter 1312 represents software, firmware, hardware, or a combinationthereof that, through emulation, simulation or any other process, allowsa processor or other electronic device that does not have an x86instruction set processor or core to execute the x86 binary code 1306.

FIG. 14A schematically illustrates an example searching technique inaccordance with various embodiments that provide extended vector suffixcomparisons for Boyer-Moore searches. The example technique may be usedfor searching for a pattern P (indicated at 1402) of a length m in a setof data T (indicated at 1404). A Boyer-Moore search may be performedfrom left to right, or from right to left. In the following example, wewill assume the search is left-to-right. At the point in the patternsearch shown in FIG. 14A, the leftmost of two portions of T (T₀, T₁) waspreviously bounded by a sliding window and checked for potential matchesof P using extended vectorized comparisons (with no matches found). Forexample, one or more ordered vectorized comparisons may have beenperformed within each portion of T to search for potential matches of P.

In various embodiments, the one or more vectorized comparisons mayinclude forward vector comparisons and reverse vector comparisons. Theforward vector comparisons are represented by the top arrows and thereverse vector comparisons are represented by the bottom arrows. Invarious embodiments, the forward and reverse vector comparisons may bebetween suffixes of P and T. For instance, in the first sliding windowportion, T₀, a forward vector suffix comparison, e.g., as may beperformed using a SIMD instruction such as PCMPESTRI, was performedbetween a sixteen-byte suffix of P, P[m−16, m−1] and a sixteen-bytesuffix of T₀, T₀[m−16, m−1]. That is to say, if any initial sequence,P[m−16, m−i] (for 1≤i≤16), of the sixteen-byte suffix of P, matched anyfinal sequence T₀[m−16+j, m−1] (for 0≤j≤15), an index, if, would havebeen set to the smallest such matching value of j. Otherwise the indexwould have been set to sixteen (16). In this example and othersdescribed herein, the vector comparisons operate on sixteen bytesbecause many modern processors have registers capable of storing sixteenbytes. For example, a PCMPESTRI instruction is capable of operating onsixteen bytes at a time. However, this is not meant to be limiting, andother sizes of vectors may be vector compared where registers of othersizes are available.

A reverse vector suffix comparison was also performed, e.g., as may beperformed using a SIMD instruction such as PCMPESTRI, in the firstsliding window T₀ between a sixteen-byte suffix of P, P[m−1, m−16] and asixteen-byte suffix of T₀, T₀[m−1, m−16]. This is referred to as a“reverse” vector comparison because the suffixes of T₀ and P arecompared in reverse (as indicated by the box enclosed by a dot-dash-dotperimeter line). That is to say, if any initial sequence, P[m−1, m−16+i](for 0≤i≤15), of the byte-reversed sixteen-byte suffix of P, matched anyfinal sequence T₀[m−j, m−16] (for 1≤j≤16), an index, jr, would have beenset to the largest such matching value of j. Otherwise the index, jr,would have been set to sixteen (i.e. m).

In various embodiments, the forward vector comparison may provide a16-byte “safety zone” where the sliding window overlaps no more than 16bytes of the suffix of P. In various embodiments, the reverse vectorcomparison may provide another safety zone, e.g., where the slidingwindow overshoots an instance of P by no more than 15 bytes. The resultof both vector comparisons in the sliding window T₀ was failure (asindicated by the “≠” symbols in the arrows). This may indicate that nopotential match of P was found within the sliding window correspondingto T₀. As a result, the sliding window was shifted (to the right in FIG.14A) by a distance d, and the vector comparisons were performed again onthe next portion of T, T₁.

It will be appreciated that when a potential match of P is found withinthe sliding window the sliding window may be shifted (to the right inFIG. 14A) by a distance less than d, for example, if the index jr isequal to 16 (i.e. m) then first (leftmost) potential match is at anindex of m−1+jf. Otherwise if jr is not equal to m, then first(leftmost) potential match is at an index of m−1−jr. Such indices may begenerated by some embodiments of extended vector suffix comparisons forBoyer-Moore searches. It will also be appreciated that for someembodiments, when more than one potential match of P is found within thesliding window, e.g. both indices jr and jf are less than m, then bothleftmost potential match indices, m−1−jr and m−1+jf, may be returned asresults of the search.

In various embodiments, particularly where no potential match of P isfound within a given sliding window, the sliding window shift distance dmay be greater than the length m of P. For example, in some embodimentsd may be equal to two times a width of the vectorized comparisons (e.g.,a register length) supported by a processor of a computing system, minusone. The increased sliding window shift distance may lead to vectorizedpattern searching being more efficient than conventional Boyer-Moorealgorithm variants. For instance, using vectorized comparisons tocompare multiple data units of the pattern P with multiple-data-unitswithin each sliding window T_(k) may reduce a likelihood that a slidingwindow will be shifted by smaller distances dictated by conventionBoyer-Moore algorithm variants, e.g., by one data unit, or up to alength of a register, minus one data unit.

In various embodiments, including the example technique of FIG. 14A, itmay not be necessary to consult a bad character table to determine asliding window shift distance. Rather, so long as no potential matchesof P are found in a current sliding window, a constant shift distance dmay be used. In various embodiments, this sliding window shift distanced may be greater than the pattern suffix length m. There also may beless sliding window shifts over an entire course of a pattern searchperformed as shown in FIG. 14A than there would be using conventionalBoyer-Moore pattern searching algorithm. For example, there may be areduced number of sliding window shifts by distances of one data unitand/or a register length minus one data unit. Accordingly, a patternsearch performed as shown in FIG. 14A may require less overall slidingwindow shifts than a conventional Boyer-Moore pattern searchingalgorithm. Pattern searches for Boyer-Moore searches performed as shownin FIG. 14A may be supported through executable machine instructionsaccording to some embodiments of extended vector suffix comparisons.

FIG. 14B illustrates an embodiment of an apparatus 1401 to provideextended vector suffix comparisons for Boyer-Moore searches. Apparatus1401 comprises comparison logic 1405 to compare, for equality, thevalues of input elements T0-T15 corresponding to a set of data T (asindicated at 1404) and P0-P15 corresponding to a pattern P (indicated at1402) of a length m. The results of these comparisons may be aggregatedaccording to an equal ordered substring search operation, at least inpart by AND logic gates 1415, 1416, 1417, . . . 1429 of an equal orderedsubstring search function unit 1403 to set bits of a mask 1440 result,B15, B16, B17, . . . B29 and B30, according to a forward vector suffixcomparison. The results of the comparisons may also be aggregatedaccording to an equal ordered substring search operation, at least inpart by AND logic gates 1415, 1414, 1413, . . . 1411 of unit 1403 to setbits of the mask 1440 result, B15, B14, B13, . . . B1 and B0, accordingto a reversed vector suffix comparison. A NOR logic gate 1431 mayoptionally set mask 1440 result, B31, when none of the other mask 1440results, B0-B30 are set. Mask 1440 results, B0-B31 may be encoded intoan index 1460 by an indexing functional unit 1407. It will beappreciated that one of skill in the art may easily modify such detailssuch as AND or NOR logic gates, in some embodiments. Embodiments ofindexing unit 1407 may comprise, one-set exclusivity logic gates toselect a least significant (or a most significant) set bit of mask 1440results, B0-B31 as inputs I0-I31 to encoder 1450, which produces outputbits O4-O0 and stores the resulting index 1460. Such an index 1460and/or mask 1440 may be returned as a result of an extended vectorsuffix comparison instruction such as a forward-reverse comparison asperformed in FIG. 14A.

It will be appreciated that in some embodiments such comparisons forequality may be done with less than the illustrated number of equalitycomparisons and irrespective of the data type of the elements. It willalso be appreciated that some embodiments may support extended vectorsuffix comparisons for Boyer-Moore searches without significantlyincreasing implementation costs. An instruction such as the extendedforward-reverse vector suffix comparison instruction may be implementedby a sequence of micro-operations in some embodiments, including forexample, one or more micro-operations to reverse the ordering of dataelements of both the pattern source operand and the target sourceoperand, and a plurality of micro-operations to perform packedcomparisons of strings with equal ordered aggregation on the originalordering and on the reversed ordering. Thus, with relatively littleadditional hardware, extended vector suffix comparison functionality maybe provided, in such a way that design tradeoffs may be made betweenprocessing speed, power consumption, die area, etc.

FIG. 15A schematically illustrates an alternative example searchingtechnique in accordance with various embodiments that provide extendedvector suffix comparisons for Boyer-Moore searches. The exampletechnique may be used for searching for a pattern P (1502) in a set ofdata T (1504). In this embodiment, two or more forward vectorcomparisons may be performed within each sliding window. In some cases,these two or more forward vector comparisons may be performedback-to-back. In this example, the pattern P has a length m of sixteen,though this is not required. The sixteen bytes of the pattern P, may beforward vector compared to the first sixteen bytes of T within a slidingwindow. For instance, in the first sliding window portion, T₀, a forwardvector suffix comparison, e.g., as may be performed using a SIMDinstruction such as PCMPESTRI, may be performed between a sixteen-bytesuffix of P, P[m−16, m−1] and the first sixteen-bytes of a thirty-twobyte suffix of T, T₀[d−32, d−17]. That is to say, if any initialsequence, P[m−16, m−i] (for 1≤i≤16), of the sixteen-byte suffix of P,matches any final sequence T₀[d−32+j, d−17] (for 0≤j≤15), an index, j1,may be set to the smallest such matching value of j. Otherwise theindex, j₁, would be set to sixteen (16). Similarly, the sixteen bytes ofthe pattern P, P[m−16 to m−1], may be forward vector compared to thelast sixteen bytes of T, T₀[d−16 to d−1], within the sliding window, andan index, j2, may be set to the smallest such matching value of j.Otherwise the index, j2, would be set to sixteen (16). If no potentialmatch to P is found by either vector comparison, then the sliding windowmay be shifted by a distance d. In some embodiments, more than twoback-to-back vector comparisons may be performed within a sliding windowto increase its size, reducing a number of sliding window shifts.

It will be appreciated that when a potential match of P is found withinthe sliding window the sliding window may be shifted (to the right inFIG. 14A) by a distance less than d, for example, if the index j1 isequal to 16 (i.e. m) then first (leftmost) potential match is at anindex of m+j2. Otherwise if j1 is not equal to m, then first (leftmost)potential match is at an index of j1. Such indices may be generated bysome embodiments of extended vector suffix comparisons for Boyer-Mooresearches.

FIG. 15B illustrates an alternative embodiment of an apparatus 1501 toprovide extended vector suffix comparisons for Boyer-Moore searches.Apparatus 1501 comprises comparison logic 1505 to compare, for equality,the values of input elements T0-T31 corresponding to a set of data T (asindicated at 1504) and P0-P15 corresponding to a pattern P (indicated at1502) of a length m. The results of these comparisons may be aggregatedaccording to an equal ordered substring search operation, at least inpart by AND logic gates 1510, 1511, 1512, . . . 1514 of an equal orderedsubstring search function unit 1503 to set bits of a mask 1540 result,B0, B1, B2, . . . B14 and B15, according to a first vector suffixcomparison. The results of the comparisons may also be aggregatedaccording to an equal ordered substring search operation, at least inpart by AND logic gates 1516, 1517, 1518, . . . 1530 of unit 1503 to setbits of the mask 1540 result, B16, B17, B18, . . . B30 and B31,according to a second vector suffix comparison. A NOR logic gate 1532may optionally set mask 1540 result, B32, when none of the other mask1540 results, B0-B31 are set. Mask 1540 results, B0-B32 may be encodedinto an index 1560 by an indexing functional unit 1507. It will beappreciated that one of skill in the art may easily modify such detailssuch as AND or NOR logic gates, in some embodiments. Embodiments ofindexing unit 1507 may comprise, one-set exclusivity logic gates toselect a least significant (or a most significant) set bit of mask 1540results, B0-B32 as inputs I0-I32 to encoder 1550, which produces outputbits O5-O0 and stores the resulting index 1560. Such an index 1560and/or mask 1540 may be returned as a result of an extended vectorsuffix comparison instruction such as a two-forward comparison asperformed in FIG. 15A.

It will be appreciated that forward and reverse equal orderedcomparisons such as those illustrated in FIGS. 14A-15B may be combinedin some embodiments to perform extended vector suffix comparisons of anyconvenient length. Also, it will be again appreciated that in someembodiments such comparisons for equality may be done with more or lessthan the illustrated number of equality comparisons and irrespective ofthe data type of the elements. It will be further appreciated that someembodiments may support extended vector suffix comparisons forBoyer-Moore searches without significantly increasing implementationcosts. An instruction such as the extended two-forward vector suffixcomparison instruction may be implemented by a sequence ofmicro-operations in some embodiments, including for example, a pluralityof micro-operations to perform packed comparisons of strings with equalordered aggregation. Thus, with relatively little additional hardware,extended vector suffix comparison functionality may be provided, in sucha way that design tradeoffs may be made between processing speed, powerconsumption, die area, etc.

FIG. 16 illustrates a flow diagram for one embodiment of a process 1601to provide extended vector suffix comparisons for Boyer-Moore searches.Process 1601 and other processes herein disclosed are performed byprocessing blocks that may comprise dedicated hardware or software orfirmware operation codes executable by general purpose machines or byspecial purpose machines or by a combination of both.

In processing block 1610 of process 1601, execution of an instruction toprovide extended vector suffix comparisons for Boyer-Moore searchesstarts by comparing m data elements of a pattern source operand witheach data element of a target source operand for equality. In processingblock 1620 a first ordered aggregation operation is performed from aportion of the comparisons with the m data elements of the patternsource operand. In processing block 1630 a second ordered aggregationoperation is performed from a portion of the comparisons with the m dataelements of the pattern source operand. In processing block 1640 aresult of the first and second aggregation operations is storedindicating where (or whether or not) a possible match exists between them data elements of the pattern source operand and d data elementpositions of the target, relative to data elements of the target sourceoperand.

It will be appreciated that while the processing blocks of process 1601and other processes herein disclosed are illustrated as sequentialoperations, in some embodiments they may also be performed in differentorders or concurrently.

FIG. 17 illustrates a flow diagram for an alternative embodiment of aprocess 1701 to provide extended vector suffix comparisons forBoyer-Moore searches. In processing block 1710 of process 1701,execution of an instruction to provide extended vector suffixcomparisons for Boyer-Moore searches starts by comparing m data elementsof a pattern source operand with each of m data elements of a portion ofa target source operand, for example, as in comparison logic 1405. Inprocessing block 1720 a forward equal ordered aggregation operation isperformed from a portion of the comparisons with the m data elements ofthe pattern source operand. In processing block 1730 a reverse equalordered aggregation operation is performed from a portion of thecomparisons with the m data elements of the pattern source operand, forexample as in equal ordered substring search function unit 1403. Inprocessing block 1740 a result of the forward and reverse aggregationoperations is stored, for example, a mask 1440 or an index 1460,indicating where (or whether or not) a possible match exists between them data elements of the pattern source operand and d data elementpositions of the target, relative to data elements of the target sourceoperand.

FIG. 18 illustrates a flow diagram for another alternative embodiment ofa process 1801 to provide extended vector suffix comparisons forBoyer-Moore searches. In processing block 1810 of process 1801,execution of an instruction to provide extended vector suffixcomparisons for Boyer-Moore searches starts by comparing m data elementsof a pattern source operand with each of m data elements of a portion ofa target source operand, for example, as in comparison logic 1505. Inprocessing block 1820 a first equal ordered aggregation operation isperformed from the comparisons with the m data elements of the patternsource operand. In processing block 1730 the m data elements of thepattern source operand are compared with each of m data elements ofanother portion of a target source operand. In processing block 1840 asecond equal ordered aggregation operation is performed from thecomparisons with the m data elements of the pattern source operand, forexample as in equal ordered substring search function unit 1503. Inprocessing block 1850 a result of the first and second aggregationoperations is stored, for example, a mask 1540 or an index 1560,indicating where (or whether or not) a possible match exists between them data elements of the pattern source operand and d data elementpositions of the target, relative to data elements of the target sourceoperand.

It will be appreciated that in accordance with some embodiments ofprocesses herein disclosed, pattern searches for Boyer-Moore searchesmay be supported through executable machine instructions for extendedvector suffix comparisons, which may require less overall sliding windowshifts than a conventional Boyer-Moore pattern searching algorithm. Itwill also be appreciated that embodiments may support extended vectorsuffix comparisons for Boyer-Moore searches without significantlyincreasing implementation costs. An instruction such as an extendedforward-reverse vector suffix comparison instruction, for example, or anextended two-forward vector suffix comparison instruction, as anotherexample, may be implemented with relatively little additional hardwareor alternatively by a sequence of micro-operations in some embodiments.Thus, with relatively little additional hardware, extended vector suffixcomparison functionality may be provided, in such a way that designtradeoffs may be made between processing speed, power consumption, diearea, etc.

Embodiments of the mechanisms disclosed herein may be implemented inhardware, software, firmware, or a combination of such implementationapproaches. Embodiments of the invention may be implemented as computerprograms or program code executing on programmable systems comprising atleast one processor, a storage system (including volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device.

Program code may be applied to input instructions to perform thefunctions described herein and generate output information. The outputinformation may be applied to one or more output devices, in knownfashion. For purposes of this application, a processing system includesany system that has a processor, such as, for example; a digital signalprocessor (DSP), a microcontroller, an application specific integratedcircuit (ASIC), or a microprocessor.

The program code may be implemented in a high level procedural or objectoriented programming language to communicate with a processing system.The program code may also be implemented in assembly or machinelanguage, if desired. In fact, the mechanisms described herein are notlimited in scope to any particular programming language. In any case,the language may be a compiled or interpreted language.

One or more aspects of at least one embodiment may be implemented byrepresentative instructions stored on a machine-readable medium whichrepresents various logic within the processor, which when read by amachine causes the machine to fabricate logic to perform the techniquesdescribed herein. Such representations, known as “IP cores” may bestored on a tangible, machine readable medium and supplied to variouscustomers or manufacturing facilities to load into the fabricationmachines that actually make the logic or processor.

Such machine-readable storage media may include, without limitation,non-transitory, tangible arrangements of articles manufactured or formedby a machine or device, including storage media such as hard disks, anyother type of disk including floppy disks, optical disks, compact diskread-only memories (CD-ROMs), compact disk rewritable's (CD-RWs), andmagneto-optical disks, semiconductor devices such as read-only memories(ROMs), random access memories (RAMs) such as dynamic random accessmemories (DRAMs), static random access memories (SRAMs), erasableprogrammable read-only memories (EPROMs), flash memories, electricallyerasable programmable read-only memories (EEPROMs), magnetic or opticalcards, or any other type of media suitable for storing electronicinstructions.

Accordingly, embodiments of the invention also include non-transitory,tangible machine-readable media containing instructions or containingdesign data, such as Hardware Description Language (HDL), which definesstructures, circuits, apparatuses, processors and/or system featuresdescribed herein. Such embodiments may also be referred to as programproducts.

In some cases, an instruction converter may be used to convert aninstruction from a source instruction set to a target instruction set.For example, the instruction converter may translate (e.g., using staticbinary translation, dynamic binary translation including dynamiccompilation), morph, emulate, or otherwise convert an instruction to oneor more other instructions to be processed by the core. The instructionconverter may be implemented in software, hardware, firmware, or acombination thereof. The instruction converter may be on processor, offprocessor, or part on and part off processor.

Thus, techniques for performing one or more instructions according to atleast one embodiment are disclosed. While certain exemplary embodimentshave been described and shown in the accompanying drawings, it is to beunderstood that such embodiments are merely illustrative of and notrestrictive on the broad invention, and that this invention not belimited to the specific constructions and arrangements shown anddescribed, since various other modifications may occur to thoseordinarily skilled in the art upon studying this disclosure. In an areaof technology such as this, where growth is fast and furtheradvancements are not easily foreseen, the disclosed embodiments may bereadily modifiable in arrangement and detail as facilitated by enablingtechnological advancements without departing from the principles of thepresent disclosure or the scope of the accompanying claims.

What is claimed is:
 1. A processor comprising: a first registercomprising a first plurality of m data fields to store values of m dataelements: a decode stage to decode a first instruction specifying: apattern source operand specifying the first register; and a targetsource operand; and an execution unit, responsive to the decoded firstinstruction, to: perform a first equal ordered aggregation operation onresults from comparisons of each of the m data elements of the patternsource operand with each of data elements of a first set of dataelements of the target source operand; perform a second equal orderedaggregation operation on results from comparisons of each of the m dataelements of the pattern source operand with each of data elements of asecond set of data elements of the target source operand; determine andstore a first index for the first equal ordered aggregation operation,wherein the first index comprises a size of a first matching sequenceshared by the pattern source operand and the first set of data elementsof the target source operand; determine and store a second index for thesecond equal ordered aggregation operation, wherein the second indexcomprises a size of a second matching sequence shared by the patternsource operand and the second set of data elements of the target sourceoperand; and determine, based on the first index and the second index, asliding window shift distance relative to data elements of the targetsource operand.
 2. The processor of claim 1, wherein the first indexfurther comprises a location of a least significant element position ofa possible suffix match to the m data elements of the pattern sourceoperand relative to the first set of data elements of the target sourceoperand.
 3. The processor of claim 1, wherein the first index furthercomprises a mask indicating any element position of a possible suffixmatch to the m data elements of the pattern source operand relative tothe first set of data elements of the target source operand.
 4. Theprocessor of claim 1, wherein a total number of data elements in thefirst set of data elements of the target source operand and the secondset of data elements of the target source operand is greater than m. 5.The processor of claim 1, wherein the first equal ordered aggregationoperation and the second equal ordered aggregation operation occur in aforward order of the data elements for both the pattern source operandand the target source operand, and wherein the second set of dataelements of the target source operand is contiguous to the first set ofdata elements of the target source operand.
 6. The processor of claim 1,wherein a number of the data elements in the first set of data elementsof the target source operand is equal to a number of the data elementsin the second set of data elements of the target source operand.
 7. Theprocessor of claim 1, wherein a number of data elements in the first setof data elements of the target source operand is equal to m.
 8. Theprocessor of claim 1, wherein for the first equal ordered aggregationoperation an order of the data elements is a forward order for both thepattern source operand and the first set of data elements of the targetsource operand, and for the second equal ordered aggregation operationan order of the data elements is a reverse order for both the patternsource operand and the second set of data elements of the target sourceoperand, and wherein the second set of data elements of the targetsource operand is identical to the first set of data elements of thetarget source operand.
 9. The processor of claim 1, wherein the firstequal ordered aggregation operation and the second equal orderedaggregation operation occur in a reverse order for both the patternsource operand and the target source operand, and wherein the second setof data elements of the target source operand is contiguous to the firstset of data elements of the target source operand.
 10. A non-transitorymachine-readable medium to record functional descriptive materialincluding a first executable instruction, which when executed by amachine, causes the machine to: perform a first equal orderedaggregation operation on results from comparisons of each of m dataelements of a pattern source operand with each of data elements of afirst set of data elements of a target source operand; perform a secondequal ordered aggregation operation on results from comparisons of eachof the m data elements of the pattern source operand with each of dataelements of a second set of data elements of the target source operand;determine and store a first index for the first equal orderedaggregation operation, wherein the first index comprises a size of amatching sequence shared by the pattern source operand and the first setof data elements of the target source operand; determine and store asecond index for the second equal ordered aggregation operation, whereinthe second index comprises a size of a second matching sequence sharedby the pattern source operand and the second set of data elements of thetarget source operand; and determine, based on the first index and thesecond index, a sliding window shift distance relative to data elementsof the target source operand.
 11. The machine-readable medium of claim10, wherein for the first equal ordered aggregation operation an orderof the data elements is a forward order for both the pattern sourceoperand and first set of data elements of the target source operand, andfor the second equal ordered aggregation operation an order of the dataelements is a reverse order for both the pattern source operand and thesecond set of data elements of the target source operand, and whereinthe second set of data elements of the target source operand isidentical to the first set of data elements of the target sourceoperand.
 12. The machine-readable medium of claim 11, wherein a numberof data elements in the first set of data elements of the target sourceoperand is equal to m.
 13. The machine-readable medium of claim 10,wherein a total number of data elements in the first set of dataelements of the target source operand and the second set of dataelements of the target source operand is greater than m.
 14. Themachine-readable medium of claim 10, wherein the first index furthercomprises a mask indicating any element position of a possible suffixmatch with the m data elements of the pattern source operand relative tothe first set of data elements of the target source operand.
 15. Themachine-readable medium of claim 10, wherein the first index furthercomprises a location of a least significant element position of apossible suffix match with the m data elements of the pattern sourceoperand relative to the first set of data elements of the target sourceoperand.
 16. The machine-readable medium of claim 10, wherein the firstequal ordered aggregation operation and the second equal orderedaggregation operation occur in a reverse order for both the patternsource operand and the target source operand, and wherein the second setof data elements of the target source operand is contiguous to the firstset of data elements of the target source operand.
 17. A processingsystem comprising: a memory; and a first plurality of processors, eachof the first plurality of processors comprising: a first registercomprising a first plurality of m data fields to store values of m dataelements; a decode stage to decode a first instruction specifying: apattern source operand specifying the first register, an immediateoperand, and a target source operand; and an execution unit, responsiveto the decoded first instruction, to: perform a first equal orderedaggregation operation on results from comparisons of each of the m dataelements of the pattern source operand with each of data elements of afirst set of data elements of the target source operand; perform asecond equal ordered aggregation operation on results from comparisonsof each of the m data elements of the pattern source operand with eachof data elements of a second set of data elements of the target sourceoperand; determine and store a first index for the first equal orderedaggregation operation, wherein the first index comprises a size of afirst matching sequence shared by the pattern source operand and thefirst set of data elements of the target source operand; determine andstore a second index for the second equal ordered aggregation operation,wherein the second index comprises a size of a second matching sequenceshared by the pattern source operand and the second set of data elementsof the target source operand; and determine, based on the first indexand the second index, a sliding window shift distance relative to dataelements of the target source operand.
 18. The processing system ofclaim 17, wherein a number of data elements in the first set of dataelements of the target source operand is equal to m.
 19. The processingsystem of claim 18, wherein for the first equal ordered aggregationoperation an order of the data elements is a forward order for both thepattern source operand and the first set of data elements of the targetsource operand, and for the second equal ordered aggregation operationan order of the data elements is a reverse order for both the patternsource operand and the second set of data elements of the target sourceoperand, and wherein the second set of data elements of the targetsource operand is identical to the first set of data elements of thetarget source operand.
 20. The processing system of claim 17, whereinthe first instruction is decoded to produce one or more micro-operationsto reverse an ordering of data elements of both the pattern sourceoperand and the target source operand, and a plurality ofmicro-operations to perform packed comparisons of strings with equalordered aggregation.
 21. The processing system of claim 20, wherein thefirst index further comprises a location of a least significant elementposition of a possible suffix match with the m data elements of thepattern source operand relative to the first set of data elements of thetarget source operand.
 22. The processing system of claim 20, whereinthe first index further comprises a mask indicating any element positionof a possible suffix match with the m data elements of the patternsource operand relative to the first set of data elements of the targetsource operand.
 23. The processing system of claim 17, wherein the firstequal ordered aggregation operation and the second equal orderedaggregation operation occur in a reverse order for both the patternsource operand and the target source operand, and wherein the second setof data elements of the target source operand is contiguous to the firstset of data elements of the target source operand.